purduedb/PostgreSQL-V

Fast vector search in PostgreSQL

23
/ 100
Experimental

This project helps database administrators and developers implement extremely fast similarity searches within their PostgreSQL databases. It takes existing vector embeddings (numerical representations of data like images, text, or audio) stored in PostgreSQL and allows for rapid querying to find the most similar items. This is ideal for anyone managing a PostgreSQL database who needs to power applications requiring instant 'find me things like this' capabilities, such as recommendation engines, semantic search, or anomaly detection.

Use this if you are a database administrator or backend developer looking to enhance PostgreSQL with high-performance vector similarity search capabilities.

Not ideal if you are looking for a standalone vector database and do not primarily use PostgreSQL for your data storage.

database-administration similarity-search vector-embeddings recommendation-systems semantic-search
No License No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 7 / 25
Community 0 / 25

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17

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Language

PLpgSQL

License

Last pushed

Jan 26, 2026

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