diff --git a/datasets/datasets.json b/datasets/datasets.json
index ec6cf94d..ba9cfcbc 100644
--- a/datasets/datasets.json
+++ b/datasets/datasets.json
@@ -85,6 +85,14 @@
       "labels": "keyword",
       "submitter": "keyword"
     }
+  },
+    {
+    "name": "arxiv-titles-384-angular-no-filters",
+    "vector_size": 384,
+    "distance": "cosine",
+    "type": "tar",
+    "path": "arxiv-titles-384-angular-no-filters/arxiv_no_filters",
+    "link": "https://storage.googleapis.com/ann-filtered-benchmark/datasets/arxiv_no_filters.tar.gz"
   },
   {
     "name": "random-match-keyword-100-angular-filters",
diff --git a/engine/clients/redis/search.py b/engine/clients/redis/search.py
index 4c6d0c92..04b868b2 100644
--- a/engine/clients/redis/search.py
+++ b/engine/clients/redis/search.py
@@ -21,7 +21,13 @@ def init_client(cls, host, distance, connection_params: dict, search_params: dic
 
     @classmethod
     def search_one(cls, vector, meta_conditions, top) -> List[Tuple[int, float]]:
-        prefilter_condition, params = cls.parser.parse(meta_conditions)
+        conditions = cls.parser.parse(meta_conditions)
+        if conditions is None:
+            prefilter_condition = "*"
+            params = {}
+        else:
+            prefilter_condition, params = conditions
+
         q = (
             Query(
                 f"{prefilter_condition}=>[KNN $K @vector $vec_param EF_RUNTIME $EF AS vector_score]"
diff --git a/engine/clients/weaviate/search.py b/engine/clients/weaviate/search.py
index 5adcda4b..126e95b3 100644
--- a/engine/clients/weaviate/search.py
+++ b/engine/clients/weaviate/search.py
@@ -26,9 +26,25 @@ def search_one(cls, vector, meta_conditions, top) -> List[Tuple[int, float]]:
         query = cls.client.query.get(
             WEAVIATE_CLASS_NAME, ["_additional {id distance}"]
         ).with_near_vector(near_vector)
+
+        is_geo_query = False
         if where_conditions is not None:
+            operands = where_conditions["operands"]
+            is_geo_query = any(
+                operand["operator"] == "WithinGeoRange" for operand in operands
+            )
             query = query.with_where(where_conditions)
-        res = (query.with_limit(top).do())["data"]["Get"][WEAVIATE_CLASS_NAME]
+
+        query_obj = query.with_limit(top)
+        if is_geo_query:
+            # weaviate can't handle geo queries in python due to excess quotes in generated queries
+            gql_query = query_obj.build()
+            for field in ("geoCoordinates", "latitude", "longitude", "distance", "max"):
+                gql_query = gql_query.replace(f'"{field}"', field)  # get rid of quotes
+            response = cls.client.query.raw(gql_query)
+        else:
+            response = query_obj.do()
+        res = response["data"]["Get"][WEAVIATE_CLASS_NAME]
 
         id_score_pairs: List[Tuple[int, float]] = []
         for obj in res:
diff --git a/engine/clients/weaviate/upload.py b/engine/clients/weaviate/upload.py
index 9ef17a1a..eca19221 100644
--- a/engine/clients/weaviate/upload.py
+++ b/engine/clients/weaviate/upload.py
@@ -1,4 +1,3 @@
-import time
 import uuid
 from typing import List, Optional
 
@@ -20,6 +19,18 @@ def init_client(cls, host, distance, connection_params, upload_params):
         cls.upload_params = upload_params
         cls.connection_params = connection_params
 
+    @staticmethod
+    def _update_geo_data(data_object):
+        keys = data_object.keys()
+        for key in keys:
+            if isinstance(data_object[key], dict):
+                if lat := data_object[key].pop("lat", None):
+                    data_object[key]["latitude"] = lat
+                if lon := data_object[key].pop("lon", None):
+                    data_object[key]["longitude"] = lon
+
+        return data_object
+
     @classmethod
     def upload_batch(
         cls, ids: List[int], vectors: List[list], metadata: List[Optional[dict]]
@@ -33,6 +44,7 @@ def upload_batch(
 
         with cls.client.batch as batch:
             for id_, vector, data_object in zip(ids, vectors, metadata):
+                data_object = cls._update_geo_data(data_object)
                 batch.add_data_object(
                     data_object=data_object or {},
                     class_name=WEAVIATE_CLASS_NAME,
diff --git a/poetry.lock b/poetry.lock
index 17dcdc93..1f75193f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1804,4 +1804,4 @@ validators = ">=0.18.2,<0.20.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8,<3.11"
-content-hash = "fa147cdc33d2be1373deb6755e3f8f89582b0cede7adbf245b201e0c89e10627"
+content-hash = "fa147cdc33d2be1373deb6755e3f8f89582b0cede7adbf245b201e0c89e10627"
\ No newline at end of file
diff --git a/sync.sh b/sync.sh
old mode 100644
new mode 100755
index 169e6724..c0b540f6
--- a/sync.sh
+++ b/sync.sh
@@ -9,4 +9,6 @@ rsync -avP \
    --exclude='__pycache__' \
    --exclude='frontend' \
    --exclude='.idea' \
+   --exclude='.git' \
+   --exclude='datasets/*/' \
    . $1:./projects/vector-db-benchmark/