pgvector is an open-source vector similarity search extension for PostgreSQL, allowing the storage of vectors alongside structured data in a single, well-established database. While it lacks some advanced features of specialized vector databases, it benefits from ACID compliance, point-in-time recovery and other robust features of PostgreSQL. With the rise of generative AI-powered applications, we see a growing pattern of storing and efficiently searching embedding vectors for similarities, which pgvector addresses effectively. With pgvector’s growing use in production environments, especially where teams are already using a cloud provider that offers managed PostgreSQL, and its proven ability to meet common vector search needs without requiring a separate vector store, we're confident in its potential. Our teams have found it valuable in projects comparing structured and unstructured data, demonstrating its potential for broader adoption, and we're therefore moving it to the Trial ring.
With the rise of Generative AI-powered applications, we see a pattern of storing and efficiently searching embeddings vectors for similarities. pgvector is an open-source vector similarity search extension for PostgreSQL. We quite like it because it enables us to search the embeddings in PostgreSQL without moving the data to another store just for similarity search. Although there are several specialized vector search engines, we want you to assess pgvector.
