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pgvector

Open-source vector similarity search extension for PostgreSQL at enterprise scale

vector searchPostgreSQLopen sourceAI infrastructure
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About

pgvector enables enterprises to perform efficient vector similarity search directly within PostgreSQL, simplifying AI and machine learning workflows by integrating vector search with relational data. It supports scalable, compliant deployments with the security and reliability of PostgreSQL, facilitating advanced analytics and AI-driven applications without additional infrastructure.

This description came from a bulk import and has not yet been checked against the vendor's own page. Treat it as unverified.

Enterprise Readiness

from cataloged data

Not scored. Nobody has checked this entry against pgvector’s own site yet, so the signals below are unverified and we will not turn them into a rating. The breakdown shows what our record holds.

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityStrong

Flexible deployment: Cloud, On-Premise, Hybrid, Self-Hosted

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

6 documented use cases

Company MaturityNot disclosed

Company maturity not disclosed

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Enterprise Use Cases

Semantic search in enterprise applications
Recommendation engines
Natural language processing pipelines
Image and video similarity search
AI-powered customer support
Fraud detection using vector embeddings

Integrations

PostgreSQLSupabaseHasuraTimescaleDBDjango ORMSQLAlchemyNode.jsPython

How pgvector compares

ToolReadinessPricingDeploymentComplianceIntegrations
pgvectorNot scoredOpen SourceCloud, On-Premise, Hybrid, Self-Hosted8
MilvusNot scoredOpen SourceCloud, On-Premise, Hybrid, Self-Hosted8
ZillizNot scoredEnterpriseCloud, On-Premise, Hybrid, Self-Hosted7
Elasticsearch Vector67 · StrongEnterpriseCloud, On-Premise, Hybrid8

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is pgvector used for?

pgvector is open-source vector similarity search extension for PostgreSQL at enterprise scale. It is commonly used for semantic search in enterprise applications, recommendation engines, natural language processing pipelines, and image and video similarity search.

Is pgvector free, and how is it priced?

pgvector is open source and can be self-hosted at no licensing cost. Commercial support or hosted tiers may also be available from the vendor.

How can pgvector be deployed?

pgvector supports Cloud, On-Premise, Hybrid, and Self-Hosted deployment. On-premise and self-hosted options support data-residency and air-gapped requirements.

What does pgvector integrate with?

pgvector documents 8 integrations, including PostgreSQL, Supabase, Hasura, TimescaleDB, Django ORM, and SQLAlchemy.

Is pgvector enterprise-ready?

Based on cataloged data, pgvector has an Enterprise Readiness score of 58/100 (Established tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingOpen Source
DeploymentCloud, On-Premise, Hybrid, Self-Hosted
CategoryData & MLOps

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