If code and methodology is what you're looking for, there's some great open-source vector databases out there. Milvus: https://github.com/milvus-io/milvus http

If code and methodology is what you're looking for, there's some great open-source vector databases out there. Milvus: https://github.com/milvus-io/milvus https://github.com/milvus-io/milvus Qdrant: https://github.com/qdrant/qdrant https://github.com/qdrant/qdrant Weaviate: https://github.com/semi-technologies/weaviate https://github.com/semi-technologies/weaviate Milvus seems to be the most advanced and best performing vector DB (https://www.farfetchtechblog.com/en/blog/post/powering-ai-with-vector-databases-a-benchmark-part-i/ https://www.farfetchtechblog.com/en/blog/post/powering-ai-wi...). Haven't seen Qdrant benchmarks yet but cool project nonetheless. FWIW, these open source projects are how I got into the area of vector similarity search to begin with.