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KNOWLEDGE

pgvector

A PostgreSQL extension that adds vector similarity search directly inside an existing relational database.

  • Category Knowledge

Technology Overview

What Is pgvector?

pgvector is an open-source PostgreSQL extension that adds a vector data type and similarity-search operations directly inside a PostgreSQL database, rather than requiring a separate, dedicated vector-database system.

At a Glance

Key Capabilities

  • pgvector enables approximate-nearest-neighbor and exact vector similarity search alongside standard relational queries in the same database, useful when a client already runs PostgreSQL and wants to avoid adding a separate data store.
How Cortex Uses It
Cortex Texas AI uses pgvector when a client already runs PostgreSQL and a dedicated vector database would add unnecessary operational overhead, keeping embeddings and relational business data together in one system.
  • Accuracy
  • Latency
  • Cost
  • Privacy
  • Integration
  • Multimodal Needs
  • Reasoning Depth

Connectivity

Integration Scenarios

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    Common integration scenarios include organizations with an existing PostgreSQL-based system of record that want to add retrieval-augmented AI features without introducing new infrastructure.

Model Selection

The Right Model Depends on the Workload

pgvector is one of several vector-search options Cortex Texas AI can integrate with; a dedicated vector database such as Qdrant, Pinecone or Weaviate may be a better fit at larger scale or higher query volume.

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