Forge SQL ORM

Forge-SQL-ORM is an ORM designed for working with @forge/sql in Atlassian Forge. It is built on top of Drizzle ORM and provides advanced capabilities for working with relational databases inside Forge.

Key Features

• ✅ Custom Drizzle Driver for direct integration with @forge/sql
• ✅ Local Cache System (Level 1) for in-memory query optimization within single resolver invocation scope
• ✅ Global Cache System (Level 2) with cross-invocation caching, automatic cache invalidation and context-aware operations (using @forge/kvs )
• ✅ Type-Safe Query Building: Write SQL queries with full TypeScript support
• ✅ Supports complex SQL queries with joins and filtering using Drizzle ORM
• ✅ Advanced Query Methods: selectFrom(), selectDistinctFrom(), selectCacheableFrom(), selectDistinctCacheableFrom() for all-column queries with field aliasing
• ✅ Raw SQL Execution: execute() and executeCacheable() methods for direct SQL queries with local and global caching
• ✅ Common Table Expressions (CTEs): with() method for complex queries with subqueries
• ✅ Schema migration support, allowing automatic schema evolution
• ✅ Automatic entity generation from MySQL/tidb databases
• ✅ Automatic migration generation from MySQL/tidb databases
• ✅ Drop Migrations Generate a migration to drop all tables and clear migrations history for subsequent schema recreation
• ✅ Schema Fetching Development-only web trigger to retrieve current database schema and generate SQL statements for schema recreation
• ✅ Ready-to-use Migration Triggers Built-in web triggers for applying migrations, dropping tables (development-only), and fetching schema (development-only) with proper error handling and security controls
• ✅ Optimistic Locking Ensures data consistency by preventing conflicts when multiple users update the same record
• ✅ Query Plan Analysis: Detailed execution plan analysis and optimization insights

Table of Contents

🚀 Getting Started

• Key Features
• Usage Approaches
• Installation
• CLI Commands | CLI Documentation
• Quick Start

📖 Core Features

• Field Name Collision Prevention
• Drizzle Usage with forge-sql-orm
• Direct Drizzle Usage with Custom Driver

🗄️ Database Operations

• Fetch Data
• Modify Operations
• SQL Utilities

⚡ Caching System

• Setting Up Caching with @forge/kvs
• Global Cache System (Level 2)
• Cache Context Operations
• Local Cache Operations (Level 1)
• Cache-Aware Query Operations
• Manual Cache Management

🔒 Advanced Features

• Optimistic Locking
• Query Analysis and Performance Optimization
• Date and Time Types

🛠️ Development Tools

• CLI Commands | CLI Documentation
• Web Triggers for Migrations
• Step-by-Step Migration Workflow
• Drop Migrations

📚 Examples

• Simple Example
• Drizzle Driver Example
• Optimistic Locking Example
• Dynamic Queries Example
• Query Analysis Example
• Organization Tracker Example
• Checklist Example

📚 Reference

• ForgeSqlOrmOptions
• Migration Guide

🚀 Quick Navigation

New to Forge-SQL-ORM? Start here:

• Quick Start - Get up and running in 5 minutes
• Installation - Complete setup guide
• Basic Usage Examples - Simple query examples

Looking for specific features?

• Global Cache System (Level 2) - Cross-invocation persistent caching
• Local Cache System (Level 1) - In-memory invocation caching
• Optimistic Locking - Data consistency
• Migration Tools - Database migrations
• Query Analysis - Performance optimization

Looking for practical examples?

• Simple Example - Basic ORM usage
• Optimistic Locking Example - Real-world conflict handling
• Organization Tracker Example - Complex relationships
• Checklist Example - Jira integration

Usage Approaches

1. Full Forge-SQL-ORM Usage

import ForgeSQL from "forge-sql-orm";
const forgeSQL = new ForgeSQL();

Best for: Advanced features like optimistic locking, automatic versioning, and automatic field name collision prevention in complex queries.

2. Direct Drizzle Usage

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver } from "forge-sql-orm";
const db = drizzle(forgeDriver);

Best for: Simple Modify operations without optimistic locking. Note that you need to manually patch drizzle patchDbWithSelectAliased for select fields to prevent field name collisions in Atlassian Forge SQL.

3. Local Cache Optimization

import ForgeSQL from "forge-sql-orm";
const forgeSQL = new ForgeSQL();

// Optimize repeated queries within a single invocation
await forgeSQL.executeWithLocalContext(async () => {
  // Multiple queries here will benefit from local caching
  const users = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // This query will use local cache (no database call)
  const cachedUsers = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // Using new methods for better performance
  const usersFrom = await forgeSQL.selectFrom(users)
    .where(eq(users.active, true));
  
  // This will use local cache (no database call)
  const cachedUsersFrom = await forgeSQL.selectFrom(users)
    .where(eq(users.active, true));
  
  // Raw SQL with local caching
  const rawUsers = await forgeSQL.execute(
    "SELECT id, name FROM users WHERE active = ?", 
    [true]
  );
});

Best for: Performance optimization of repeated queries within resolvers or single invocation contexts.

Field Name Collision Prevention in Complex Queries

When working with complex queries involving multiple tables (joins, inner joins, etc.), Atlassian Forge SQL has a specific behavior where fields with the same name from different tables get collapsed into a single field with a null value. This is not a Drizzle ORM issue but rather a characteristic of Atlassian Forge SQL's behavior.

Forge-SQL-ORM provides two ways to handle this:

Using Forge-SQL-ORM

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();

// Automatic field name collision prevention
await forgeSQL
  .select({user: users, order: orders})
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));

Using Direct Drizzle

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver, patchDbWithSelectAliased } from "forge-sql-orm";

const db = patchDbWithSelectAliased(drizzle(forgeDriver));

// Manual field name collision prevention
await db
  .selectAliased({user: users, order: orders})
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));

Important Notes

• This is a specific behavior of Atlassian Forge SQL, not Drizzle ORM
• For complex queries involving multiple tables, it's recommended to always specify select fields and avoid using select() without field selection
• The solution automatically creates unique aliases for each field by prefixing them with the table name
• This ensures that fields with the same name from different tables remain distinct in the query results

Installation

Forge-SQL-ORM is designed to work with @forge/sql and requires some additional setup to ensure compatibility within Atlassian Forge.

✅ Step 1: Install Dependencies

Basic installation (without caching):

npm install forge-sql-orm @forge/sql drizzle-orm -S

With caching support:

npm install forge-sql-orm @forge/sql @forge/kvs drizzle-orm -S

This will:

• Install Forge-SQL-ORM (the ORM for @forge/sql)
• Install @forge/sql, the Forge database layer
• Install @forge/kvs, the Forge Key-Value Store for caching (optional, only needed for caching features)
• Install Drizzle ORM and its MySQL driver
• Install TypeScript types for MySQL
• Install forge-sql-orm-cli A command-line interface tool for managing Atlassian Forge SQL migrations and model generation with Drizzle ORM integration.

Quick Start

1. Basic Setup

import ForgeSQL from "forge-sql-orm";

// Initialize ForgeSQL
const forgeSQL = new ForgeSQL();

// Simple query
const users = await forgeSQL.select().from(users);

2. With Caching (Optional)

import ForgeSQL from "forge-sql-orm";

// Initialize with caching
const forgeSQL = new ForgeSQL({
  cacheEntityName: "cache",
  cacheTTL: 300
});

// Cached query
const users = await forgeSQL.selectCacheable({ id: users.id, name: users.name })
  .from(users).where(eq(users.active, true));

3. Local Cache Optimization

// Optimize repeated queries within a single invocation
await forgeSQL.executeWithLocalContext(async () => {
  const users = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // This query will use local cache (no database call)
  const cachedUsers = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // Using new methods for better performance
  const usersFrom = await forgeSQL.selectFrom(users)
    .where(eq(users.active, true));
  
  // Raw SQL with local caching
  const rawUsers = await forgeSQL.execute(
    "SELECT id, name FROM users WHERE active = ?", 
    [true]
  );
});

4. Next Steps

• Full Installation Guide - Complete setup instructions
• Core Features - Learn about key capabilities
• Global Cache System (Level 2) - Cross-invocation caching features
• Local Cache System (Level 1) - In-memory caching features
• API Reference - Complete API documentation

Drizzle Usage with forge-sql-orm

If you prefer to use Drizzle ORM with the additional features of Forge-SQL-ORM (like optimistic locking and caching), you can use the enhanced API:

import ForgeSQL from "forge-sql-orm";
const forgeSQL = new ForgeSQL();

// Versioned operations with cache management (recommended)
await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [userData]);
await forgeSQL.modifyWithVersioningAndEvictCache().updateById(updateData, Users);

// Versioned operations without cache management
await forgeSQL.modifyWithVersioning().insert(Users, [userData]);
await forgeSQL.modifyWithVersioning().updateById(updateData, Users);

// Non-versioned operations with cache management
await forgeSQL.insertAndEvictCache(Users).values(userData);
await forgeSQL.updateAndEvictCache(Users).set(updateData).where(eq(Users.id, 1));

// Basic Drizzle operations (cache context aware)
await forgeSQL.insert(Users).values(userData);
await forgeSQL.update(Users).set(updateData).where(eq(Users.id, 1));

// Direct Drizzle access
const db = forgeSQL.getDrizzleQueryBuilder();
const users = await db.select().from(users);

// Using new methods for enhanced functionality
const usersFrom = await forgeSQL.selectFrom(users)
  .where(eq(users.active, true));

const usersDistinct = await forgeSQL.selectDistinctFrom(users)
  .where(eq(users.active, true));

const usersCacheable = await forgeSQL.selectCacheableFrom(users)
  .where(eq(users.active, true));

// Raw SQL execution
const rawUsers = await forgeSQL.execute(
  "SELECT * FROM users WHERE active = ?", 
  [true]
);

// Raw SQL with caching
const cachedRawUsers = await forgeSQL.executeCacheable(
  "SELECT * FROM users WHERE active = ?", 
  [true], 
  300
);

// Common Table Expressions (CTEs)
const userStats = await forgeSQL
  .with(
    forgeSQL.selectFrom(users).where(eq(users.active, true)).as('activeUsers'),
    forgeSQL.selectFrom(orders).where(eq(orders.status, 'completed')).as('completedOrders')
  )
  .select({
    totalActiveUsers: sql`COUNT(au.id)`,
    totalCompletedOrders: sql`COUNT(co.id)`
  })
  .from(sql`activeUsers au`)
  .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`));

This approach gives you direct access to all Drizzle ORM features while still using the @forge/sql backend with enhanced caching and versioning capabilities.

Direct Drizzle Usage with Custom Driver

If you prefer to use Drizzle ORM directly without the additional features of Forge-SQL-ORM (like optimistic locking), you can use the custom driver:

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver, patchDbWithSelectAliased } from "forge-sql-orm";

// Initialize drizzle with the custom driver and patch it for aliased selects
const db = patchDbWithSelectAliased(drizzle(forgeDriver));

// Use drizzle directly
const users = await db.select().from(users);
const users = await db.selectAliased(getTableColumns(users)).from(users);
const users = await db.selectAliasedDistinct(getTableColumns(users)).from(users);
await db.insert(users)...;
await db.update(users)...;
await db.delete(users)...;
// Use drizzle with kvs cache
const users = await db.selectAliasedCacheable(getTableColumns(users)).from(users);
const users = await db.selectAliasedDistinctCacheable(getTableColumns(users)).from(users);
await db.insertAndEvictCache(users)...;
await db.updateAndEvictCache(users)...;
await db.deleteAndEvictCache(users)...;

// Use drizzle with kvs cache context
await forgeSQL.executeWithCacheContext(async () => {
  await db.insertWithCacheContext(users)...;
  await db.updateWithCacheContext(users)...;
  await db.deleteWithCacheContext(users)...;
  // invoke without cache
   const users = await db.selectAliasedCacheable(getTableColumns(users)).from(users);  
  // Cache is cleared only once at the end for all affected tables
});

// Using new methods with direct drizzle
const usersFrom = await forgeSQL.selectFrom(users)
  .where(eq(users.active, true));

const usersDistinct = await forgeSQL.selectDistinctFrom(users)
  .where(eq(users.active, true));

const usersCacheable = await forgeSQL.selectCacheableFrom(users)
  .where(eq(users.active, true));

// Raw SQL execution
const rawUsers = await forgeSQL.execute(
  "SELECT * FROM users WHERE active = ?", 
  [true]
);

// Raw SQL with caching
const cachedRawUsers = await forgeSQL.executeCacheable(
  "SELECT * FROM users WHERE active = ?", 
  [true], 
  300
);

Setting Up Caching with @forge/kvs (Optional)

The caching system is optional and only needed if you want to use cache-related features. To enable the caching system, you need to install the required dependency and configure your manifest.

How Caching Works

To use caching, you need to use Forge-SQL-ORM methods that support cache management:

Methods that perform cache eviction after execution and in cache context (batch eviction):

• forgeSQL.insertAndEvictCache()
• forgeSQL.updateAndEvictCache()
• forgeSQL.deleteAndEvictCache()
• forgeSQL.modifyWithVersioningAndEvictCache()
• forgeSQL.getDrizzleQueryBuilder().insertAndEvictCache()
• forgeSQL.getDrizzleQueryBuilder().updateAndEvictCache()
• forgeSQL.getDrizzleQueryBuilder().deleteAndEvictCache()

Methods that participate in cache context only (batch eviction):

• All methods except the default Drizzle methods:
  • forgeSQL.insert()
  • forgeSQL.update()
  • forgeSQL.delete()
  • forgeSQL.modifyWithVersioning()
  • forgeSQL.getDrizzleQueryBuilder().insertWithCacheContext()
  • forgeSQL.getDrizzleQueryBuilder().updateWithCacheContext()
  • forgeSQL.getDrizzleQueryBuilder().deleteWithCacheContext()

Methods do not do evict cache, better do not use with cache feature:

• forgeSQL.getDrizzleQueryBuilder().insert()
• forgeSQL.getDrizzleQueryBuilder().update()
• forgeSQL.getDrizzleQueryBuilder().delete()

Cacheable methods:

• forgeSQL.selectCacheable()
• forgeSQL.selectDistinctCacheable()
• forgeSQL.getDrizzleQueryBuilder().selectAliasedCacheable()
• forgeSQL.getDrizzleQueryBuilder().selectAliasedDistinctCacheable()

Cache context example:

await forgeSQL.executeWithCacheContext(async () => {
  // These methods participate in batch cache clearing
  await forgeSQL.insert(Users).values(userData);
  await forgeSQL.update(Users).set(updateData).where(eq(Users.id, 1));
  await forgeSQL.delete(Users).where(eq(Users.id, 1));
  // Cache is cleared only once at the end for all affected tables
});

The diagram below shows the lifecycle of a cacheable query in Forge-SQL-ORM:

1. Resolver calls forge-sql-orm with a SQL query and parameters.
2. forge-sql-orm generates a cache key = hash(sql, parameters).
3. It asks @forge/kvs for an existing cached result.
   • Cache hit → result is returned immediately.
   • Cache miss / expired → query is executed against @forge/sql.
4. Fresh result is stored in @forge/kvs with TTL and returned to the caller.

The diagram below shows how Evict Cache works in Forge-SQL-ORM:

1. Data modification is executed through @forge/sql (e.g., UPDATE users ...).
2. After a successful update, forge-sql-orm queries the cache entity by using the sql field with filter.contains("users") to find affected cached queries.
3. The returned cache entries are deleted in batches (up to 25 per transaction).
4. Once eviction is complete, the update result is returned to the resolver.
5. Note: Expired entries are not processed here — they are cleaned up separately by the scheduled cache cleanup trigger using the expiration index.

The diagram below shows how Scheduled Expiration Cleanup works:

1. A periodic scheduler (Forge trigger) runs cache cleanup independently of data modifications.
2. forge-sql-orm queries the cache entity by the expiration index to find entries with expiration < now.
3. Entries are deleted in batches (up to 25 per transaction) until the page is empty; pagination is done with a cursor (e.g., 100 per page).
4. This keeps the cache footprint small and prevents stale data accumulation.

The diagram below shows how Cache Context works:

executeWithCacheContext(fn) lets you group multiple data modifications and perform one consolidated cache eviction at the end:

1. The context starts with an empty affectedTables set.
2. Each successful INSERT/UPDATE/DELETE inside the context registers its table name in affectedTables.
3. Reads inside the same context that target tables present in affectedTables will bypass the cache (read-through to SQL) to avoid serving stale data. These reads also do not write back to cache until eviction completes.
4. On context completion, affectedTables is de-duplicated and used to build one combined KVS query over the sql field with filter.or(filter.contains("<t1>"), filter.contains("<t2>"), ...), returning all impacted cache entries in a single scan (paged by cursor, e.g., 100/page).
5. Matching cache entries are deleted in batches (≤25 per transaction) until the page is exhausted; then the next page is fetched via the cursor.
6. Expiration is handled separately by the scheduled cleanup and is not part of the context flow.

Important Considerations

@forge/kvs Limits: Please review the official @forge/kvs quotas and limits before implementing caching.

Caching Guidelines:

• Don't cache everything - be selective about what to cache
• Don't cache simple and fast queries - sometimes direct query is faster than cache
• Consider data size and frequency of changes
• Monitor cache usage to stay within quotas
• Use appropriate TTL values

Step 1: Install Dependencies

npm install @forge/kvs -S

Step 2: Configure Manifest

Add the storage entity configuration and scheduler trigger to your manifest.yml:

modules:
  scheduledTrigger:
    - key: clear-cache-trigger
      function: clearCache
      interval: fiveMinute
  storage:
    entities:
      - name: cache
        attributes:
          sql:
            type: string
          expiration:
            type: integer
          data:
            type: string
        indexes:
          - sql
          - expiration
  sql:
    - key: main
      engine: mysql
  function:
    - key: clearCache
      handler: index.clearCache

// Example usage in your Forge app
import { clearCacheSchedulerTrigger } from "forge-sql-orm";

export const clearCache = () => {
  return clearCacheSchedulerTrigger({ 
    cacheEntityName: "cache",
  });
};

Step 3: Configure ORM Options

Set the cache entity name in your ForgeSQL configuration:

const options = {
  cacheEntityName: "cache", // Must match the entity name in manifest.yml
  cacheTTL: 300, // Default cache TTL in seconds (5 minutes)
  cacheWrapTable: true, // Wrap table names with backticks in cache keys
  // ... other options
};

const forgeSQL = new ForgeSQL(options);

Important Notes:

• The cacheEntityName must exactly match the name in your manifest storage entities
• The entity attributes (sql, expiration, data) are required for proper cache functionality
• Indexes on sql and expiration improve cache lookup performance
• Cache data is automatically cleaned up based on TTL settings
• No additional permissions are required beyond standard Forge app permissions

Complete Setup Examples

Basic setup (without caching):

package.json:

npm install forge-sql-orm @forge/sql drizzle-orm -S

manifest.yml:

modules:
  sql:
    - key: main
      engine: mysql

index.ts:

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();

// simple insert
await forgeSQL.insert(Users, [userData]);
// Use versioned operations without caching
await forgeSQL.modifyWithVersioning().insert(Users, [userData]);
const users = await forgeSQL.select({id: Users.id});

With caching support:

npm install forge-sql-orm @forge/sql @forge/kvs drizzle-orm -S

manifest.yml:

modules:
  scheduledTrigger:
    - key: clear-cache-trigger
      function: clearCache
      interval: fiveMinute
  storage:
    entities:
      - name: cache
        attributes:
          sql:
            type: string
          expiration:
            type: integer
          data:
            type: string
        indexes:
          - sql
          - expiration
  sql:
    - key: main
      engine: mysql
  function:
    - key: clearCache
      handler: index.clearCache

index.ts:

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL({
    cacheEntityName: "cache"
});

import {clearCacheSchedulerTrigger} from "forge-sql-orm";
import {getTableColumns} from "drizzle-orm";

export const clearCache = () => {
    return clearCacheSchedulerTrigger({
        cacheEntityName: "cache",
    });
};


// Now you can use caching features
const usersData = await forgeSQL.selectCacheable(getTableColumns(users)).from(users).where(eq(users.active, true))

// simple insert
await forgeSQL.insertAndEvictCache(users, [userData]);
// Use versioned operations with caching
await forgeSQL.modifyWithVersioningAndEvictCache().insert(users, [userData]);

// use Cache Context
const data = await forgeSQL.executeWithCacheContextAndReturnValue(async () => {
    // after insert mark users to evict
    await forgeSQL.insert(users, [userData]);
       // after insertAndEvictCache mark orders to evict
    await forgeSQL.insertAndEvictCache(orders, [order1, order2]);
    // execute query and put result to local cache
    await forgeSQL.selectCacheable({userId: users.id, userName: users.name, orderId: orders.id, orderName: orders.name})
        .from(users)
        .innerJoin(orders, eq(orders.userId, users.id)).where(eq(users.active, true))
    // use local cache without @forge/kvs and @forge/sql
    return await forgeSQL.selectCacheable({userId: users.id, userName: users.name, orderId: orders.id, orderName: orders.name})
        .from(users)
        .innerJoin(orders, eq(orders.userId, users.id)).where(eq(users.active, true))
})
// execute query and put result to kvs cache
await forgeSQL.selectCacheable({userId: users.id, userName: users.name, orderId: orders.id, orderName: orders.name})
        .from(users)
        .innerJoin(orders, eq(orders.userId, users.id)).where(eq(users.active, true))

// get result from @foge/kvs cache without real @forge/sql call
await forgeSQL.selectCacheable({userId: users.id, userName: users.name, orderId: orders.id, orderName: orders.name})
        .from(users)
        .innerJoin(orders, eq(orders.userId, users.id)).where(eq(users.active, true))

// use Local Cache for performance optimization
const optimizedData = await forgeSQL.executeWithLocalCacheContextAndReturnValue(async () => {
    // First query - hits database and caches result
    const users = await forgeSQL.select({id: users.id, name: users.name})
        .from(users).where(eq(users.active, true));
    
    // Second query - uses local cache (no database call)
    const cachedUsers = await forgeSQL.select({id: users.id, name: users.name})
        .from(users).where(eq(users.active, true));
    
    // Using new methods for better performance
    const usersFrom = await forgeSQL.selectFrom(users)
        .where(eq(users.active, true));
    
    // This will use local cache (no database call)
    const cachedUsersFrom = await forgeSQL.selectFrom(users)
        .where(eq(users.active, true));
    
    // Raw SQL with local caching
    const rawUsers = await forgeSQL.execute(
        "SELECT id, name FROM users WHERE active = ?", 
        [true]
    );
    
    // Insert operation - evicts local cache
    await forgeSQL.insert(users).values({name: 'New User', active: true});
    
    // Third query - hits database again and caches new result
    const updatedUsers = await forgeSQL.select({id: users.id, name: users.name})
        .from(users).where(eq(users.active, true));
    
    return { users, cachedUsers, updatedUsers, usersFrom, cachedUsersFrom, rawUsers };
});

Choosing the Right Method - ForgeSQL ORM

When to Use Each Approach

Method	Use Case	Versioning	Cache Management
modifyWithVersioningAndEvictCache()	High-concurrency scenarios with Cache support	✅ Yes	✅ Yes
modifyWithVersioning()	High-concurrency scenarios	✅ Yes	Cache Context
insertAndEvictCache()	Simple inserts	❌ No	✅ Yes
updateAndEvictCache()	Simple updates	❌ No	✅ Yes
deleteAndEvictCache()	Simple deletes	❌ No	✅ Yes
insert/update/delete	Basic Drizzle operations	❌ No	Cache Context
selectFrom()	All-column queries with field aliasing	❌ No	Local Cache
selectDistinctFrom()	Distinct all-column queries with field aliasing	❌ No	Local Cache
selectCacheableFrom()	All-column queries with field aliasing and caching	❌ No	Local + Global Cache
selectDistinctCacheableFrom()	Distinct all-column queries with field aliasing and caching	❌ No	Local + Global Cache
execute()	Raw SQL queries with local caching	❌ No	Local Cache
executeCacheable()	Raw SQL queries with local and global caching	❌ No	Local + Global Cache
with()	Common Table Expressions (CTEs)	❌ No	Local Cache

Choosing the Right Method - Direct Drizzle

When to Use Each Approach

Method	Use Case	Versioning	Cache Management
insertWithCacheContext/insertWithCacheContext/updateWithCacheContext	Basic Drizzle operations	❌ No	Cache Context
insertAndEvictCache()	Simple inserts without conflicts	❌ No	✅ Yes
updateAndEvictCache()	Simple updates without conflicts	❌ No	✅ Yes
deleteAndEvictCache()	Simple deletes without conflicts	❌ No	✅ Yes
insert/update/delete	Basic Drizzle operations	❌ No	❌ No
selectFrom()	All-column queries with field aliasing	❌ No	Local Cache
selectDistinctFrom()	Distinct all-column queries with field aliasing	❌ No	Local Cache
selectCacheableFrom()	All-column queries with field aliasing and caching	❌ No	Local + Global Cache
selectDistinctCacheableFrom()	Distinct all-column queries with field aliasing and caching	❌ No	Local + Global Cache
execute()	Raw SQL queries with local caching	❌ No	Local Cache
executeCacheable()	Raw SQL queries with local and global caching	❌ No	Local + Global Cache
with()	Common Table Expressions (CTEs)	❌ No	Local Cache
where Cache context - allows you to batch cache invalidation events and bypass cache reads for affected tables.

Step-by-Step Migration Workflow

1. Generate initial schema from an existing database

   npx forge-sql-orm-cli generate:model --dbName testDb --output ./database/schema

   (This is done only once when setting up the project)

2. Create the first migration

   npx forge-sql-orm-cli migrations:create --dbName testDb --entitiesPath ./database/schema --output ./database/migration

   (This initializes the database migration structure, also done once)

3. Deploy to Forge and verify that migrations work

   • Deploy your Forge app with migrations.
   • Run migrations using a Forge web trigger or Forge scheduler.

4. Modify the database (e.g., add a new column, index, etc.)

   • Use DbSchema or manually alter the database schema.

5. Update the migration

   npx forge-sql-orm-cli migrations:update --dbName testDb --entitiesPath ./database/schema --output ./database/migration

   • ⚠️ Do NOT update schema before this step!
   • If schema is updated first, the migration will be empty!

6. Deploy to Forge and verify that the migration runs without issues

   • Run the updated migration on Forge.

7. Update the schema

   npx forge-sql-orm-cli generate:model --dbName testDb --output ./database/schema

8. Repeat steps 4-7 as needed

⚠️ WARNING:

• Do NOT swap steps 7 and 5! If you update schema before generating a migration, the migration will be empty!
• Always generate the migration first, then update the schema.

Drop Migrations

The Drop Migrations feature allows you to completely reset your database schema in Atlassian Forge SQL. This is useful when you need to:

• Start fresh with a new schema
• Reset all tables and their data
• Clear migration history
• Ensure your local schema matches the deployed database

Important Requirements

Before using Drop Migrations, ensure that:

1. Your local schema exactly matches the current database schema deployed in Atlassian Forge SQL
2. You have a backup of your data if needed
3. You understand that this operation will delete all tables and data

Usage

1. First, ensure your local schema matches the deployed database:

   npx forge-sql-orm-cli generate:model --output ./database/schema

2. Generate the drop migration:

   npx forge-sql-orm-cli migrations:drop --entitiesPath ./database/schema --output ./database/migration

3. Deploy and run the migration in your Forge app:

   import migrationRunner from "./database/migration";
   import { MigrationRunner } from "@forge/sql/out/migration";
   
   const runner = new MigrationRunner();
   await migrationRunner(runner);
   await runner.run();

4. After dropping all tables, you can create a new migration to recreate the schema:

   npx forge-sql-orm-cli migrations:create --entitiesPath ./database/schema --output ./database/migration --force

   The --force parameter is required here because we're creating a new migration after dropping all tables.

Example Migration Output

The generated drop migration will look like this:

import { MigrationRunner } from "@forge/sql/out/migration";

export default (migrationRunner: MigrationRunner): MigrationRunner => {
    return migrationRunner
        .enqueue("v1_MIGRATION0", "ALTER TABLE `orders` DROP FOREIGN KEY `fk_orders_users`")
        .enqueue("v1_MIGRATION1", "DROP INDEX `idx_orders_user_id` ON `orders`")
        .enqueue("v1_MIGRATION2", "DROP TABLE IF EXISTS `orders`")
        .enqueue("v1_MIGRATION3", "DROP TABLE IF EXISTS `users`")
        .enqueue("MIGRATION_V1_1234567890", "DELETE FROM __migrations");
};

⚠️ Important Notes

• This operation is irreversible - all data will be lost
• Make sure your local schema is up-to-date with the deployed database
• Consider backing up your data before running drop migrations
• The migration will clear the __migrations table to allow for fresh migration history
• Drop operations are performed in the correct order: first foreign keys, then indexes, then tables

---

Date and Time Types

When working with date and time fields in your models, you should use the custom types provided by Forge-SQL-ORM to ensure proper handling of date/time values. This is necessary because Forge SQL has specific format requirements for date/time values:

Date type	Required Format	Example
DATE	YYYY-MM-DD	2024-09-19
TIME	HH:MM:SS[.fraction]	06:40:34
TIMESTAMP	YYYY-MM-DD HH:MM:SS[.fraction]	2024-09-19 06:40:34.999999

// ❌ Don't use standard Drizzle date/time types
export const testEntityTimeStampVersion = mysqlTable('test_entity', {
  id: int('id').primaryKey().autoincrement(),
  time_stamp: timestamp('times_tamp').notNull(),
  date_time: datetime('date_time').notNull(),
  time: time('time').notNull(),
  date: date('date').notNull(),
});

// ✅ Use Forge-SQL-ORM custom types instead
import { forgeDateTimeString, forgeDateString, forgeTimestampString, forgeTimeString } from 'forge-sql-orm'

export const testEntityTimeStampVersion = mysqlTable('test_entity', {
  id: int('id').primaryKey().autoincrement(),
  time_stamp: forgeTimestampString('times_tamp').notNull(),
  date_time: forgeDateTimeString('date_time').notNull(),
  time: forgeTimeString('time').notNull(),
  date: forgeDateString('date').notNull(),
});

Why Custom Types?

The custom types in Forge-SQL-ORM handle the conversion between JavaScript Date objects and Forge SQL's required string formats automatically. Without these custom types, you would need to manually format dates like this:

// Without custom types, you'd need to do this manually:
const date = moment().format("YYYY-MM-DD");
const time = moment().format("HH:mm:ss.SSS");
const timestamp = moment().format("YYYY-MM-DDTHH:mm:ss.SSS");

Our custom types provide:

• Automatic conversion between JavaScript Date objects and Forge SQL's required string formats
• Consistent date/time handling across your application
• Type safety for date/time fields
• Proper handling of timezone conversions
• Support for all Forge SQL date/time types (datetime, timestamp, date, time)

Available Custom Types

• forgeDateTimeString - For datetime fields (YYYY-MM-DD HH:MM:SS[.fraction])
• forgeTimestampString - For timestamp fields (YYYY-MM-DD HH:MM:SS[.fraction])
• forgeDateString - For date fields (YYYY-MM-DD)
• forgeTimeString - For time fields (HH:MM:SS[.fraction])

Each type ensures that the data is properly formatted according to Forge SQL's requirements while providing a clean, type-safe interface for your application code.

Connection to ORM

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();

or

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver } from "forge-sql-orm";

// Initialize drizzle with the custom driver
const db = drizzle(forgeDriver);

// Use drizzle directly
const users = await db.select().from(users);

Fetch Data

Basic Fetch Operations

// Using forgeSQL.select()
const user = await forgeSQL
    .select({user: users})
    .from(users);

// Using forgeSQL.selectDistinct()
const user = await forgeSQL
    .selectDistinct({user: users})
    .from(users);

// Using forgeSQL.selectCacheable()
const user = await forgeSQL
    .selectCacheable({user: users})
    .from(users);

// Using forgeSQL.selectFrom() - Select all columns with field aliasing
const user = await forgeSQL
    .selectFrom(users)
    .where(eq(users.id, 1));

// Using forgeSQL.selectDistinctFrom() - Select distinct all columns with field aliasing
const user = await forgeSQL
    .selectDistinctFrom(users)
    .where(eq(users.id, 1));

// Using forgeSQL.selectCacheableFrom() - Select all columns with field aliasing and caching
const user = await forgeSQL
    .selectCacheableFrom(users)
    .where(eq(users.id, 1));

// Using forgeSQL.selectDistinctCacheableFrom() - Select distinct all columns with field aliasing and caching
const user = await forgeSQL
    .selectDistinctCacheableFrom(users)
    .where(eq(users.id, 1));

// Using forgeSQL.execute() - Execute raw SQL with local caching
const user = await forgeSQL
    .execute("SELECT * FROM users WHERE id = ?", [1]);

// Using forgeSQL.executeCacheable() - Execute raw SQL with local and global caching
const user = await forgeSQL
    .executeCacheable("SELECT * FROM users WHERE id = ?", [1], 300);

// Using forgeSQL.getDrizzleQueryBuilder()
const user = await forgeSQL
  .getDrizzleQueryBuilder()
  .select().from(Users)
  .where(eq(Users.id, 1));

// OR using direct drizzle with custom driver
const db = drizzle(forgeDriver);
const user = await db
  .select().from(Users)
  .where(eq(Users.id, 1));
// Returns: { id: 1, name: "John Doe" }

// Using executeQueryOnlyOne for single result with error handling
const user = await forgeSQL
  .fetch()
  .executeQueryOnlyOne(
    forgeSQL
      .getDrizzleQueryBuilder()
      .select().from(Users)
      .where(eq(Users.id, 1))
  );
// Returns: { id: 1, name: "John Doe" }
// Throws error if multiple records found
// Returns undefined if no records found

// Using with aliases
// With forgeSQL
const usersAlias = alias(Users, "u");
const result = await forgeSQL
  .getDrizzleQueryBuilder()
  .select({
    userId: sql<string>`${usersAlias.id} as \`userId\``,
    userName: sql<string>`${usersAlias.name} as \`userName\``
  }).from(usersAlias);

// OR with direct drizzle
const db = drizzle(forgeDriver);
const result = await db
  .select({
    userId: sql<string>`${usersAlias.id} as \`userId\``,
    userName: sql<string>`${usersAlias.name} as \`userName\``
  }).from(usersAlias);
// Returns: { userId: 1, userName: "John Doe" }

Complex Queries

// Using joins with automatic field name collision prevention
// With forgeSQL
const orderWithUser = await forgeSQL
  .select({user: users, order: orders})
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));

// Using new selectFrom methods with joins
const orderWithUser = await forgeSQL
  .selectFrom(orders)
  .innerJoin(users, eq(orders.userId, users.id))
  .where(eq(orders.id, 1));

// Using selectCacheableFrom with joins and caching
const orderWithUser = await forgeSQL
  .selectCacheableFrom(orders)
  .innerJoin(users, eq(orders.userId, users.id))
  .where(eq(orders.id, 1));

// Using with() for Common Table Expressions (CTEs)
const userStats = await forgeSQL
  .with(
    forgeSQL.selectFrom(users).where(eq(users.active, true)).as('activeUsers'),
    forgeSQL.selectFrom(orders).where(eq(orders.status, 'completed')).as('completedOrders')
  )
  .select({
    totalActiveUsers: sql`COUNT(au.id)`,
    totalCompletedOrders: sql`COUNT(co.id)`
  })
  .from(sql`activeUsers au`)
  .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`));

// OR with direct drizzle
const db = patchDbWithSelectAliased(drizzle(forgeDriver));
const orderWithUser = await db
  .selectAliased({user: users, order: orders})
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));
// Returns: { 
//   user_id: 1, 
//   user_name: "John Doe",
//   order_id: 1,
//   order_product: "Product 1"
// }

// Using distinct with aliases
const uniqueUsers = await db
  .selectAliasedDistinct({user: users})
  .from(users);
// Returns unique users with aliased fields

// Using executeQueryOnlyOne for unique results
const userStats = await forgeSQL
  .fetch()
  .executeQueryOnlyOne(
    forgeSQL
      .getDrizzleQueryBuilder()
      .select({
        totalUsers: sql`COUNT(*) as \`totalUsers\``,
        uniqueNames: sql`COUNT(DISTINCT name) as \`uniqueNames\``
      }).from(Users)
  );
// Returns: { totalUsers: 100, uniqueNames: 80 }
// Throws error if multiple records found

Raw SQL Queries

// Using executeRawSQL for direct SQL queries
const users = await forgeSQL
  .fetch()
  .executeRawSQL<Users>("SELECT * FROM users");

// Using execute() for raw SQL with local caching
const users = await forgeSQL
  .execute("SELECT * FROM users WHERE active = ?", [true]);

// Using executeCacheable() for raw SQL with local and global caching
const users = await forgeSQL
  .executeCacheable("SELECT * FROM users WHERE active = ?", [true], 300);

// Using execute() with complex queries
const userStats = await forgeSQL
  .execute(`
    SELECT 
      u.id,
      u.name,
      COUNT(o.id) as order_count,
      SUM(o.amount) as total_amount
    FROM users u
    LEFT JOIN orders o ON u.id = o.user_id
    WHERE u.active = ?
    GROUP BY u.id, u.name
  `, [true]);

Modify Operations

Forge-SQL-ORM provides multiple approaches for Modify operations, each with different characteristics:

1. Basic Drizzle Operations (Cache Context Aware)

These operations work like standard Drizzle methods but participate in cache context when used within executeWithCacheContext():

// Basic insert (participates in cache context when used within executeWithCacheContext)
await forgeSQL.insert(Users).values({ id: 1, name: "Smith" });

// Basic update (participates in cache context when used within executeWithCacheContext)
await forgeSQL.update(Users)
  .set({ name: "Smith Updated" })
  .where(eq(Users.id, 1));

// Basic delete (participates in cache context when used within executeWithCacheContext)
await forgeSQL.delete(Users)
  .where(eq(Users.id, 1));

2. Non-Versioned Operations with Cache Management

These operations don't use optimistic locking but provide cache invalidation:

// Insert without versioning but with cache invalidation
await forgeSQL.insertAndEvictCache(Users).values({ id: 1, name: "Smith" });

// Update without versioning but with cache invalidation
await forgeSQL.updateAndEvictCache(Users)
  .set({ name: "Smith Updated" })
  .where(eq(Users.id, 1));

// Delete without versioning but with cache invalidation
await forgeSQL.deleteAndEvictCache(Users)
  .where(eq(Users.id, 1));

3. Versioned Operations with Cache Management (Recommended)

These operations use optimistic locking and automatic cache invalidation:

// Insert with versioning and cache management
const userId = await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [{ id: 1, name: "Smith" }]);

// Bulk insert with versioning
await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [
    { id: 2, name: "Smith" },
    { id: 3, name: "Vasyl" },
  ]);

// Update by ID with optimistic locking and cache invalidation
await forgeSQL.modifyWithVersioningAndEvictCache().updateById({ id: 1, name: "Smith Updated" }, Users);

// Delete by ID with versioning and cache invalidation
await forgeSQL.modifyWithVersioningAndEvictCache().deleteById(1, Users);

4. Versioned Operations without Cache Management

These operations use optimistic locking but don't manage cache:

// Insert with versioning only (no cache management)
const userId = await forgeSQL.modifyWithVersioning().insert(Users, [{ id: 1, name: "Smith" }]);

// Update with versioning only
await forgeSQL.modifyWithVersioning().updateById({ id: 1, name: "Smith Updated" }, Users);

// Delete with versioning only
await forgeSQL.modifyWithVersioning().deleteById(1, Users);

5. Legacy Modify Operations (Removed in 2.1.x)

⚠️ BREAKING CHANGE: The crud() and modify() methods have been completely removed in version 2.1.x.

// ❌ These methods no longer exist in 2.1.x
// const userId = await forgeSQL.crud().insert(Users, [{ id: 1, name: "Smith" }]);
// await forgeSQL.crud().updateById({ id: 1, name: "Smith Updated" }, Users);
// await forgeSQL.crud().deleteById(1, Users);

// ✅ Use the new methods instead
const userId = await forgeSQL.modifyWithVersioning().insert(Users, [{ id: 1, name: "Smith" }]);
await forgeSQL.modifyWithVersioning().updateById({ id: 1, name: "Smith Updated" }, Users);
await forgeSQL.modifyWithVersioning().deleteById(1, Users);

Advanced Operations

// Insert with sequence (nextVal)
import { nextVal } from "forge-sql-orm";

const user = {
  id: nextVal('user_id_seq'),
  name: "user test",
  organization_id: 1
};
const id = await forgeSQL.modifyWithVersioning().insert(appUser, [user]);

// Update with custom WHERE condition
await forgeSQL.modifyWithVersioning().updateFields(
    { name: "New Name", age: 35 },
  Users,
  eq(Users.email, "[email protected]")
);

// Insert with duplicate handling
await forgeSQL.modifyWithVersioning().insert(
  Users,
  [
    { id: 4, name: "Smith" },
    { id: 4, name: "Vasyl" },
  ],
  true
);

SQL Utilities

formatLimitOffset

The formatLimitOffset utility function is used to safely insert numeric values directly into SQL queries for LIMIT and OFFSET clauses. This is necessary because Atlassian Forge SQL doesn't support parameterized queries for these clauses.

import { formatLimitOffset } from "forge-sql-orm";

// Example usage in a query
const result = await forgeSQL
  .select()
  .from(orderItem)
  .orderBy(asc(orderItem.createdAt))
  .limit(formatLimitOffset(10))
  .offset(formatLimitOffset(350000));

// The generated SQL will be:
// SELECT * FROM order_item 
// ORDER BY created_at ASC 
// LIMIT 10 
// OFFSET 350000

Important Notes:

• The function performs type checking to prevent SQL injection
• It throws an error if the input is not a valid number
• Use this function instead of direct parameter binding for LIMIT and OFFSET clauses
• The function is specifically designed to work with Atlassian Forge SQL's limitations

Security Considerations:

• The function includes validation to ensure the input is a valid number
• This prevents SQL injection by ensuring only numeric values are inserted
• Always use this function instead of string concatenation for LIMIT and OFFSET values

Global Cache System (Level 2)

↑ Back to Top

Forge-SQL-ORM includes a sophisticated global caching system that provides cross-invocation caching - the ability to share cached data between different resolver invocations. The global cache system is built on top of @forge/kvs Custom entity store and provides persistent cross-invocation caching with automatic serialization/deserialization of complex data structures.

Cache Levels Overview

Forge-SQL-ORM implements a two-level caching architecture:

• Level 1 (Local Cache): In-memory caching within a single resolver invocation scope
• Level 2 (Global Cache): Cross-invocation persistent caching using KVS storage

This multi-level approach provides optimal performance by checking the fastest cache first, then falling back to cross-invocation persistent storage.

Cache Configuration

The caching system uses Atlassian Forge's Custom entity store to persist cache data. Each cache entry is stored as a custom entity with automatic TTL management and efficient key-based retrieval.

const options = {
  cacheEntityName: "cache", // KVS Custom entity name for cache storage
  cacheTTL: 300, // Default cache TTL in seconds (5 minutes)
  cacheWrapTable: true, // Wrap table names with backticks in cache keys
  additionalMetadata: {
    users: {
      tableName: "users",
      versionField: {
        fieldName: "updatedAt",
      }
    }
  }
};

const forgeSQL = new ForgeSQL(options);

How Caching Works with @forge/kvs

The caching system leverages Forge's Custom entity store to provide:

• Persistent Storage: Cache data survives app restarts and deployments
• Automatic TTL: Built-in expiration handling through Forge's entity lifecycle
• Efficient Retrieval: Fast key-based lookups using Forge's optimized storage
• Data Serialization: Automatic handling of complex objects and query results
• Batch Operations: Efficient bulk cache operations for better performance

// Cache entries are stored as custom entities in Forge's KVS
// Example cache key structure:
// Key: "CachedQuery_8d74bdd9d85064b72fb2ee072ca948e5"
// Value: { data: [...], expiration: 1234567890, sql: "select * from 1" }

Cache Context Operations

The cache context allows you to batch cache invalidation events and bypass cache reads for affected tables:

// Execute operations within a cache context
await forgeSQL.executeWithCacheContext(async () => {
  // All cache invalidation events are collected and executed in batch
  await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [userData]);
  await forgeSQL.modifyWithVersioningAndEvictCache().updateById(updateData, Users);
  // Cache is cleared only once at the end for all affected tables
});

// Execute with return value
const result = await forgeSQL.executeWithCacheContextAndReturnValue(async () => {
  const user = await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [userData]);
  return user;
});

// Basic operations also participate in cache context
await forgeSQL.executeWithCacheContext(async () => {
  // These operations will participate in batch cache clearing
  await forgeSQL.insert(Users).values(userData);
  await forgeSQL.update(Users).set(updateData).where(eq(Users.id, 1));
  await forgeSQL.delete(Users).where(eq(Users.id, 1));
  // Cache is cleared only once at the end for all affected tables
});

Local Cache Operations (Level 1)

Forge-SQL-ORM provides a local cache system (Level 1 cache) that stores query results in memory for the duration of a single resolver invocation. This is particularly useful for optimizing repeated queries within the same execution context(resolver invocation).

What is Local Cache?

Local cache is an in-memory caching layer that operates within a single resolver invocation scope. Unlike the global KVS cache, local cache:

• Stores data in memory using Node.js AsyncLocalStorage
• Automatically clears when the invocation completes (Resolver call)
• Provides instant access to previously executed queries in resolver invocation
• Reduces database load for repeated operations within the same invocation
• Works alongside the global KVS cache system

Key Features of Local Cache

• In-Memory Storage: Query results are cached in memory using Node.js AsyncLocalStorage
• Invocation-Scoped: Cache is automatically cleared when the invocation completes
• Automatic Eviction: Cache is cleared when insert/update/delete operations are performed
• No Persistence: Data is not stored between Invocations (unlike global KVS cache)
• Performance Optimization: Reduces database queries for repeated operations
• Simple Configuration: Works out of the box with simple setup

Usage Examples

Basic Local Cache Usage

// Execute operations within a local cache context
await forgeSQL.executeWithLocalContext(async () => {
  // First call - executes query and caches result
  const users = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // Second call - gets result from local cache (no database query)
  const cachedUsers = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // Using new selectFrom methods with local caching
  const usersFrom = await forgeSQL.selectFrom(users)
    .where(eq(users.active, true));
  
  // This will use local cache (no database call)
  const cachedUsersFrom = await forgeSQL.selectFrom(users)
    .where(eq(users.active, true));
  
  // Using execute() with local caching
  const rawUsers = await forgeSQL.execute(
    "SELECT id, name FROM users WHERE active = ?", 
    [true]
  );
  
  // This will use local cache (no database call)
  const cachedRawUsers = await forgeSQL.execute(
    "SELECT id, name FROM users WHERE active = ?", 
    [true]
  );
  
  // Insert operation - evicts local cache for users table
  await forgeSQL.insert(users).values({ name: 'New User', active: true });
  
  // Third call - executes query again and caches new result
  const updatedUsers = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
});

// Execute with return value
const result = await forgeSQL.executeWithLocalCacheContextAndReturnValue(async () => {
  // First call - executes query and caches result
  const users = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // Second call - gets result from local cache (no database query)
  const cachedUsers = await forgeSQL.select({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  return { users, cachedUsers };
});

Real-World Resolver Example

// Atlassian forge resolver with local cache optimization
const userResolver = async (req) => {
  return await forgeSQL.executeWithLocalCacheContextAndReturnValue(async () => {
    // Get user details using selectFrom (all columns with field aliasing)
    const user = await forgeSQL.selectFrom(users)
      .where(eq(users.id, args.userId));
    
    // Get user's orders using selectCacheableFrom (with caching)
    const orders = await forgeSQL.selectCacheableFrom(orders)
      .where(eq(orders.userId, args.userId));
    
    // Get user's profile using raw SQL with execute()
    const profile = await forgeSQL.execute(
      "SELECT id, bio, avatar FROM profiles WHERE user_id = ?", 
      [args.userId]
    );
    
    // Get user statistics using complex raw SQL
    const stats = await forgeSQL.execute(`
      SELECT 
        COUNT(o.id) as total_orders,
        SUM(o.amount) as total_spent,
        AVG(o.amount) as avg_order_value
      FROM orders o 
      WHERE o.user_id = ? AND o.status = 'completed'
    `, [args.userId]);
    
    // If any of these queries are repeated within the same resolver,
    // they will use the local cache instead of hitting the database
    
    return {
      ...user[0],
      orders,
      profile: profile[0],
      stats: stats[0]
    };
  });
};

Local Cache (Level 1) vs Global Cache (Level 2)

Feature	Local Cache (Level 1)	Global Cache (Level 2)
Storage	In-memory (Node.js process)	Persistent (KVS Custom Entities)
Scope	Single forge invocation	Cross-invocation (between calls)
Persistence	No (cleared on invocation end)	Yes (survives app redeploy)
Performance	Very fast (memory access)	Fast (KVS optimized storage)
Memory Usage	Low (invocation-scoped)	Higher (persistent storage)
Use Case	Invocation optimization	Cross-invocation data sharing
Configuration	None required	Requires KVS setup
TTL Support	No (invocation-scoped)	Yes (automatic expiration)
Cache Eviction	Automatic on DML operations	Manual or scheduled cleanup
Best For	Repeated queries in single invocation	Frequently accessed data across invocations

Integration with Global Cache (Level 2)

Local cache (Level 1) works alongside the global cache (Level 2) system:

// Multi-level cache checking: Level 1 → Level 2 → Database
await forgeSQL.executeWithLocalContext(async () => {
  // This will check:
  // 1. Local cache (Level 1 - in-memory)
  // 2. Global cache (Level 2 - KVS)
  // 3. Database query
  const users = await forgeSQL.selectCacheable({ id: users.id, name: users.name })
    .from(users).where(eq(users.active, true));
  
  // Using new methods with multi-level caching
  const usersFrom = await forgeSQL.selectCacheableFrom(users)
    .where(eq(users.active, true));
  
  // Raw SQL with multi-level caching
  const rawUsers = await forgeSQL.executeCacheable(
    "SELECT id, name FROM users WHERE active = ?", 
    [true], 
    300 // TTL in seconds
  );
});

Local Cache Flow Diagram

The diagram below shows how local cache works in Forge-SQL-ORM:

1. Request Start: Local cache context is initialized with empty cache
2. First Query: Cache miss → Global cache miss → Database query → Save to local cache
3. Repeated Query: Cache hit → Return cached result (no database call)
4. Data Modification: Insert/Update/Delete → Evict local cache for affected table
5. Query After Modification: Cache miss (was evicted) → Database query → Save to local cache
6. Request End: Local cache context is destroyed, all data cleared

Cache-Aware Query Operations

// Execute queries with caching
const users = await forgeSQL.modifyWithVersioningAndEvictCache().executeQuery(
  forgeSQL.select().from(Users).where(eq(Users.active, true)),
  600 // Custom TTL in seconds
);

// Execute single result queries with caching
const user = await forgeSQL.modifyWithVersioningAndEvictCache().executeQueryOnlyOne(
  forgeSQL.select().from(Users).where(eq(Users.id, 1))
);

// Execute raw SQL with caching
const results = await forgeSQL.modifyWithVersioningAndEvictCache().executeRawSQL(
  "SELECT * FROM users WHERE active = ?",
  [true],
  300 // TTL in seconds
);

// Using new methods for cache-aware operations
const usersFrom = await forgeSQL.selectCacheableFrom(Users)
  .where(eq(Users.active, true));

const usersDistinct = await forgeSQL.selectDistinctCacheableFrom(Users)
  .where(eq(Users.active, true));

// Raw SQL with local and global caching
const rawUsers = await forgeSQL.executeCacheable(
  "SELECT * FROM users WHERE active = ?",
  [true],
  300 // TTL in seconds
);

// Using with() for Common Table Expressions with caching
const userStats = await forgeSQL
  .with(
    forgeSQL.selectFrom(users).where(eq(users.active, true)).as('activeUsers'),
    forgeSQL.selectFrom(orders).where(eq(orders.status, 'completed')).as('completedOrders')
  )
  .select({
    totalActiveUsers: sql`COUNT(au.id)`,
    totalCompletedOrders: sql`COUNT(co.id)`
  })
  .from(sql`activeUsers au`)
  .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`));

Manual Cache Management

// Clear cache for specific tables
await forgeSQL.modifyWithVersioningAndEvictCache().evictCache(["users", "orders"]);

// Clear cache for specific entities
await forgeSQL.modifyWithVersioningAndEvictCache().evictCacheEntities([Users, Orders]);

Optimistic Locking

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Optimistic locking is a concurrency control mechanism that prevents data conflicts when multiple transactions attempt to update the same record concurrently. Instead of using locks, this technique relies on a version field in your entity models.

Supported Version Field Types

• datetime - Timestamp-based versioning
• timestamp - Timestamp-based versioning
• integer - Numeric version increment
• decimal - Numeric version increment

Configuration

const options = {
  additionalMetadata: {
    users: {
      tableName: "users",
      versionField: {
        fieldName: "updatedAt",
      }
    }
  }
};

const forgeSQL = new ForgeSQL(options);

Example Usage

// The version field will be automatically handled
await forgeSQL.modifyWithVersioning().updateById(
  { 
    id: 1, 
    name: "Updated Name",
    updatedAt: new Date() // Will be automatically set if not provided
  }, 
  Users
);

or with cache support

// The version field will be automatically handled
await forgeSQL.modifyWithVersioningAndEvictCache().updateById(
  { 
    id: 1, 
    name: "Updated Name",
    updatedAt: new Date() // Will be automatically set if not provided
  }, 
  Users
);

ForgeSqlOrmOptions

The ForgeSqlOrmOptions object allows customization of ORM behavior:

Option	Type	Description
logRawSqlQuery	boolean	Enables logging of raw SQL queries in the Atlassian Forge Developer Console. Useful for debugging and monitoring. Defaults to false.
disableOptimisticLocking	boolean	Disables optimistic locking. When set to true, no additional condition (e.g., a version check) is added during record updates, which can improve performance. However, this may lead to conflicts when multiple transactions attempt to update the same record concurrently.
additionalMetadata	object	Allows adding custom metadata to all entities. This is useful for tracking common fields across all tables (e.g., createdAt, updatedAt, createdBy, etc.). The metadata will be automatically added to all generated entities.
cacheEntityName	string	KVS Custom entity name for cache storage. Must match the name in your manifest.yml storage entities configuration. Required for caching functionality. Defaults to "cache".
cacheTTL	number	Default cache TTL in seconds. Defaults to 120 (2 minutes).
cacheWrapTable	boolean	Whether to wrap table names with backticks in cache keys. Defaults to true.
hints	object	SQL hints for query optimization. Optional configuration for advanced query tuning.

CLI Commands

Forge-SQL-ORM provides a command-line interface for managing database migrations and model generation.

📖 Full CLI Documentation - Complete CLI reference with all commands and options.

Quick CLI Reference

The CLI tool provides the following main commands:

• generate:model - Generate Drizzle ORM models from your database schema
• migrations:create - Create new migration files
• migrations:update - Update existing migrations with schema changes
• migrations:drop - Create migration to drop tables

Installation

npm install -g forge-sql-orm-cli

Basic Usage

# Generate models from database
forge-sql-orm-cli generate:model --dbName myapp --output ./database/entities

# Create migration
forge-sql-orm-cli migrations:create --dbName myapp --entitiesPath ./database/entities

# Update migration
forge-sql-orm-cli migrations:update --dbName myapp --entitiesPath ./database/entities

For detailed information about all available options and advanced usage, see the Full CLI Documentation.

Web Triggers for Migrations

Forge-SQL-ORM provides web triggers for managing database migrations in Atlassian Forge:

1. Apply Migrations Trigger

This trigger allows you to apply database migrations through a web endpoint. It's useful for:

• Manually triggering migrations
• Running migrations as part of your deployment process
• Testing migrations in different environments

// Example usage in your Forge app
import { applySchemaMigrations } from "forge-sql-orm";
import migration from "./migration";

export const handlerMigration = async () => {
  return applySchemaMigrations(migration);
};

Configure in manifest.yml:

  webtrigger:
     - key: invoke-schema-migration
       function: runSchemaMigration
       security:
          egress:
             allowDataEgress: false
             allowedResponses:
                - statusCode: 200
                  body: '{"body": "Migrations successfully executed"}'
  sql:
     - key: main
       engine: mysql
  function:
     - key: runSchemaMigration
       handler: index.handlerMigration

2. Drop Migrations Trigger

⚠️ WARNING: This trigger will permanently delete all data in the specified tables and clear the migrations history. This operation cannot be undone!

This trigger allows you to completely reset your database schema. It's useful for:

• Development environments where you need to start fresh
• Testing scenarios requiring a clean database
• Resetting the database before applying new migrations

Important: The trigger will drop all tables including migration.

// Example usage in your Forge app
import { dropSchemaMigrations } from "forge-sql-orm";

export const dropMigrations = () => {
  return dropSchemaMigrations();
};

Configure in manifest.yml:

  webtrigger:
     - key: drop-schema-migration
       function: dropMigrations
  sql:
     - key: main
       engine: mysql
  function:
     - key: dropMigrations
       handler: index.dropMigrations

3. Fetch Schema Trigger

⚠️ DEVELOPMENT ONLY: This trigger is designed for development environments only and should not be used in production.

This trigger retrieves the current database schema from Atlassian Forge SQL and generates SQL statements that can be used to recreate the database structure. It's useful for:

• Development environment setup
• Schema documentation
• Database structure verification
• Creating backup scripts

Security Considerations:

• This trigger exposes your database structure
• It temporarily disables foreign key checks
• It may expose sensitive table names and structures
• Should only be used in development environments

// Example usage in your Forge app
import { fetchSchemaWebTrigger } from "forge-sql-orm";

export const fetchSchema = async () => {
  return fetchSchemaWebTrigger();
};

Configure in manifest.yml:

  webtrigger:
     - key: fetch-schema
       function: fetchSchema
  sql:
     - key: main
       engine: mysql
  function:
     - key: fetchSchema
       handler: index.fetchSchema

The response will contain SQL statements like:

SET foreign_key_checks = 0;
CREATE TABLE IF NOT EXISTS users (...);
CREATE TABLE IF NOT EXISTS orders (...);
SET foreign_key_checks = 1;

4. Clear Cache Scheduler Trigger

This trigger automatically cleans up expired cache entries based on their TTL (Time To Live). It's useful for:

• Automatic cache maintenance
• Preventing cache storage from growing indefinitely
• Ensuring optimal cache performance
• Reducing storage costs

// Example usage in your Forge app
import { clearCacheSchedulerTrigger } from "forge-sql-orm";

export const clearCache = () => {
  return clearCacheSchedulerTrigger({ 
    cacheEntityName: "cache",
  });
};

Configure in manifest.yml:

  scheduledTrigger:
    - key: clear-cache-trigger
      function: clearCache
      interval: fiveMinute
  function:
    - key: clearCache
      handler: index.clearCache

Available Intervals:

• fiveMinute - Every 5 minutes
• hour - Every hour
• day - Every day

Important Notes

Security Considerations:

• The drop migrations trigger should be restricted to development environments
• The fetch schema trigger should only be used in development
• Consider implementing additional authentication for these endpoints

Best Practices:

• Always backup your data before using the drop migrations trigger
• Test migrations in a development environment first
• Use these triggers as part of your deployment pipeline
• Monitor the execution logs in the Forge Developer Console

Query Analysis and Performance Optimization

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Forge-SQL-ORM provides comprehensive query analysis tools to help you optimize your database queries and identify performance bottlenecks.

About Atlassian's Built-in Analysis Tools

Atlassian provides comprehensive query analysis tools in the development console, including:

• Basic query performance metrics
• Slow query tracking (queries over 500ms)
• Basic execution statistics
• Query history and patterns

Our analysis tools complement these built-in features by providing additional insights directly from TiDB's system schemas.

Available Analysis Tools

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();
const analyzeForgeSql = forgeSQL.analyze();

Query Plan Analysis

Query plan analysis helps you understand how your queries are executed and identify optimization opportunities.

// Example usage for analyzing a specific query
const forgeSQL = new ForgeSQL();
const analyzeForgeSql = forgeSQL.analyze();

// Analyze a Drizzle query
const plan = await analyzeForgeSql.explain(
  forgeSQL.select({
    table1: testEntityJoin1,
    table2: { name: testEntityJoin2.name, email: testEntityJoin2.email },
    count: rawSql<number>`COUNT(*)`,
    table3: {
      table12: testEntityJoin1.name,
      table22: testEntityJoin2.email,
      table32: testEntity.id
    },
  })
  .from(testEntityJoin1)
  .innerJoin(testEntityJoin2, eq(testEntityJoin1.id, testEntityJoin2.id))
);

// Analyze a raw SQL query
const rawPlan = await analyzeForgeSql.explainRaw(
  "SELECT * FROM users WHERE id = ?",
  [1]
);

// Analyze new methods
const usersFromPlan = await analyzeForgeSql.explain(
  forgeSQL.selectFrom(users).where(eq(users.active, true))
);

const usersCacheablePlan = await analyzeForgeSql.explain(
  forgeSQL.selectCacheableFrom(users).where(eq(users.active, true))
);

// Analyze Common Table Expressions (CTEs)
const ctePlan = await analyzeForgeSql.explain(
  forgeSQL
    .with(
      forgeSQL.selectFrom(users).where(eq(users.active, true)).as('activeUsers'),
      forgeSQL.selectFrom(orders).where(eq(orders.status, 'completed')).as('completedOrders')
    )
    .select({
      totalActiveUsers: sql`COUNT(au.id)`,
      totalCompletedOrders: sql`COUNT(co.id)`
    })
    .from(sql`activeUsers au`)
    .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`))
);

This analysis provides insights into:

• How the database executes your query
• Which indexes are being used
• Estimated vs actual row counts
• Resource usage at each step
• Performance optimization opportunities

Migration Guide

Migrating from 2.0.x to 2.1.x

This section covers the breaking changes introduced in version 2.1.x and how to migrate your existing code.

1. Method Renaming (BREAKING CHANGES)

Removed Methods:

• forgeSQL.modify() → REMOVED (use forgeSQL.modifyWithVersioning())
• forgeSQL.crud() → REMOVED (use forgeSQL.modifyWithVersioning())

Migration Steps:

1. Replace modify() calls:

   // ❌ Old (2.0.x) - NO LONGER WORKS
   await forgeSQL.modify().insert(Users, [userData]);
   await forgeSQL.modify().updateById(updateData, Users);
   await forgeSQL.modify().deleteById(1, Users);
   
   // ✅ New (2.1.x) - REQUIRED
   await forgeSQL.modifyWithVersioning().insert(Users, [userData]);
   await forgeSQL.modifyWithVersioning().updateById(updateData, Users);
   await forgeSQL.modifyWithVersioning().deleteById(1, Users);

2. Replace crud() calls:

   // ❌ Old (2.0.x) - NO LONGER WORKS
   await forgeSQL.crud().insert(Users, [userData]);
   await forgeSQL.crud().updateById(updateData, Users);
   await forgeSQL.crud().deleteById(1, Users);
   
   // ✅ New (2.1.x) - REQUIRED
   await forgeSQL.modifyWithVersioning().insert(Users, [userData]);
   await forgeSQL.modifyWithVersioning().updateById(updateData, Users);
   await forgeSQL.modifyWithVersioning().deleteById(1, Users);

2. New API Methods

New Methods Available:

• forgeSQL.insert() - Basic Drizzle operations
• forgeSQL.update() - Basic Drizzle operations
• forgeSQL.delete() - Basic Drizzle operations
• forgeSQL.insertAndEvictCache() - Basic Drizzle operations with evict cache after execution
• forgeSQL.updateAndEvictCache() - Basic Drizzle operations with evict cache after execution
• forgeSQL.deleteAndEvictCache() - Basic Drizzle operations with evict cache after execution
• forgeSQL.selectFrom() - All-column queries with field aliasing
• forgeSQL.selectDistinctFrom() - Distinct all-column queries with field aliasing
• forgeSQL.selectCacheableFrom() - All-column queries with field aliasing and caching
• forgeSQL.selectDistinctCacheableFrom() - Distinct all-column queries with field aliasing and caching
• forgeSQL.execute() - Raw SQL queries with local caching
• forgeSQL.executeCacheable() - Raw SQL queries with local and global caching
• forgeSQL.with() - Common Table Expressions (CTEs)

Optional Migration: You can optionally migrate to the new API methods for better performance and cache management:

// ❌ Old approach (still works)
await forgeSQL.modifyWithVersioning().insert(Users, [userData]);

// ✅ New approach (recommended for new code)
await forgeSQL.insert(Users).values(userData);
// or for versioned operations with cache management
await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [userData]);

// ✅ New query methods for better performance
const users = await forgeSQL.selectFrom(Users)
  .where(eq(Users.active, true));

const usersDistinct = await forgeSQL.selectDistinctFrom(Users)
  .where(eq(Users.active, true));

const usersCacheable = await forgeSQL.selectCacheableFrom(Users)
  .where(eq(Users.active, true));

// ✅ Raw SQL execution with caching
const rawUsers = await forgeSQL.execute(
  "SELECT * FROM users WHERE active = ?", 
  [true]
);

const cachedRawUsers = await forgeSQL.executeCacheable(
  "SELECT * FROM users WHERE active = ?", 
  [true], 
  300
);

// ✅ Common Table Expressions (CTEs)
const userStats = await forgeSQL
  .with(
    forgeSQL.selectFrom(users).where(eq(users.active, true)).as('activeUsers'),
    forgeSQL.selectFrom(orders).where(eq(orders.status, 'completed')).as('completedOrders')
  )
  .select({
    totalActiveUsers: sql`COUNT(au.id)`,
    totalCompletedOrders: sql`COUNT(co.id)`
  })
  .from(sql`activeUsers au`)
  .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`));

3. Automatic Migration Script

You can use a simple find-and-replace to migrate your code:

# Replace modify() calls
find . -name "*.ts" -o -name "*.js" | xargs sed -i 's/forgeSQL\.modify()/forgeSQL.modifyWithVersioning()/g'

# Replace crud() calls  
find . -name "*.ts" -o -name "*.js" | xargs sed -i 's/forgeSQL\.crud()/forgeSQL.modifyWithVersioning()/g'

4. Breaking Changes

Important: The old methods (modify() and crud()) have been completely removed in version 2.1.x.

• ❌ 2.1.x: Old methods are no longer available
• ✅ Migration Required: You must update your code to use the new methods

License

This project is licensed under the MIT License.
Feel free to use it for commercial and personal projects.