PostgreSQL pgvector: Getting Started and Scaling` The PostgreSQL pgvector extension allows developers to store, index, and query vector representations of text for similarity searches. To get started with pgvector, the extension needs to be installed in PostgreSQL. The process involves installing a Docker image for PostgreSQL with the pgvector extension, running it, connecting to the container, enabling the extension, and creating tables to store vectors. Developers can then insert data into these tables, assign vector representations to text descriptions, and query the vectors using distance functions such as cosine similarity, Euclidean/L2 distance, or negative inner product. The choice of index type depends on the tradeoff between build speed, query speed, and requirements for rebuild on updates. By scaling with distributed SQL databases like YugabyteDB, developers can improve storage capacity, reduce latency, and increase resilience to node, data center, or regional outages.