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pgvector

PostgreSQL extension bringing vector search to relational databases

pgvector is a PostgreSQL extension enabling vector similarity search within standard relational databases. It allows teams to leverage existing PostgreSQL infrastructure for vector operations without new specialised systems.

Pricing fromFree (open-source extension)
Best forTeams seeking vector search without introducing new database technologies
Websitegithub.com/pgvector/pgvector

Strengths and trade-offs

  • No new database to manage or maintain alongside existing PostgreSQL
  • Combines relational data with vector search seamlessly
  • Vector search performance lags dedicated vector databases
  • Scaling limitations with massive vector workloads

Appears in

Alternatives to pgvector

Pinecone
Managed vector database for semantic search at scale
#1 in Top 10 AI Search & Retrieval Engines95.0
Weaviate
Open-source vector search platform with GraphQL API
#2 in Top 10 AI Search & Retrieval Engines92.7
Milvus
Open-source vector database engineered for scalable similarity search
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OpenSearch
Open-source search and analytics engine with vector capabilities
#4 in Top 10 AI Search & Retrieval Engines88.0
Qdrant
Vector search engine optimised for extended filtering and production workloads
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Elasticsearch#6 in Top 10 AI Search & Retrieval Engines83.3

Questions about pgvector

How much does pgvector cost?

Lister lists pgvector's pricing as: Free (open-source extension).

Is pgvector free?

Yes. Its pricing reads: Free (open-source extension).

Who is pgvector best for?

pgvector is best for teams seeking vector search without introducing new database technologies.

Where does pgvector rank?

pgvector is ranked #9 in Top 10 AI Search & Retrieval Engines (Lister Score 76.3).

What are the best alternatives to pgvector?

The closest alternatives on Lister are Pinecone (#1 in Top 10 AI Search & Retrieval Engines), Weaviate (#2 in Top 10 AI Search & Retrieval Engines) and Milvus (#3 in Top 10 AI Search & Retrieval Engines).

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