we are covering our vector database performance via benchmarking against dbpedia openai dataset
we also took inspiration from the image similarity test from milvus and tested it with our database
the results are available at our website
To recreate simply download the repo and run the following
git clone https://github.com/antarys-ai/benchmark.git
cd benchmark
pip3 install -r ./requirements.txt
cd clients
python3 ./antarysdb.py
python3 ./chroma.py
this will generate results for individual results for each database in the results/DATABASE folder
This is a fairly simple test, as time goes on we will increment the complexity of the test and add more performance metrics.
Our server uses REST API, we are opting out for a gRPC server very soon, till then this benchmark is done against all the other vector database servers which uses gRPC.
Here are steps to run other databases locally, you will need docker, Antarys doesn't need docker setup, binaries are available on the website!
pip install chromadb
For more details please see this page
docker pull qdrant/qdrant
docker run -p 6333:6333 -p 6334:6334 \
-v "$(pwd)/qdrant_storage:/qdrant/storage:z" \
qdrant/qdrant
For more details please see this page
curl -sfL https://raw.githubusercontent.com/milvus-io/milvus/master/scripts/standalone_embed.sh -o standalone_embed.sh
bash standalone_embed.sh start
For more details please see this page