While building semantic search and LLM-powered apps, one needs to try out various vector databases because they differ widely in feature set, cost and other characteristics.

The Vector-io library introduces a universal open format for storing vector datasets (Vectors, along with their metadata), along with import and export scripts for a wide range of vector databases: - Pinecone - Qdrant - Milvus - GCP Vertex AI Vector Search - KDB.AI - LanceDB - DataStax Astra DB - Chroma - Turbopuffer

This will allow easier backup, snapshots, sharing of vector datasets and managing data across different vector DBs.

I'm also curating a list of publicly available datasets in this format, which can be loaded directly from HuggingFace into your favorite VectorDB: https://huggingface.co/collections/aintech/vector-io-compati...

If you have data in a vector DB, please try it out and let me know if you have feedback. Thanks!