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EDB Postgres AI

by EnterpriseDB (EDB)

Data & AnalyticsInfrastructure & CloudEnterprise PlatformGovernance & Security

A sovereign Postgres data-and-AI platform that unifies relational, analytical, vector, and agentic workloads.

Subscription · Contact for pricing·Added July 4, 2026·Updated July 4, 2026
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THE DAILY BRIEF
EDB Postgres AI

by EnterpriseDB (EDB)

Data & AnalyticsInfrastructure & CloudEnterprise PlatformGovernance & Security

A sovereign Postgres data-and-AI platform that unifies relational, analytical, vector, and agentic workloads.

Subscription · Contact for pricing

EDB Postgres AI (EDB PG AI) is a sovereign data-and-AI platform built on open-source PostgreSQL that unifies transactional, analytical, vector, and agentic workloads through a single SQL interface. It is aimed at CIOs, CTOs, and data leaders who need AI-ready infrastructure without moving data into a separate cloud or vector store.

At a Glance

Category
Data & Analytics
Pricing
Subscription, Contact for pricing
Target Market
CIOs, CTOs, Data Engineers, Database Administrators, Enterprise Architects
Founded
2004
Headquarters
Wilmington, Delaware, USA

Key Features

  • Agentic database
  • Converged analytics
  • Native vector search
  • Governance at the data layer
  • Sovereign, open-source Postgres foundation

Capabilities

text generation
image generation
video generation
code generation
workflow automation
api access
audio generation
fine tuning
agent orchestration

Use Cases

  • Unify AI and operational data
  • Reduce database sprawl
  • Ground enterprise AI agents

Ideal For

Best For

  • Running relational, analytical, vector, and agentic workloads on one Postgres foundation
  • Sovereign and on-premises AI where data cannot leave the enterprise
  • Giving AI agents governed, authorized retrieval without a separate vector database

Market Analysis

Enterprise-gradeSovereign AI operating system for the agentic era

Pros

  • Built on open-source PostgreSQL for portability and sovereignty
  • Removes the need for a separate vector store
  • Strong hardware and platform partner ecosystem

Cons

  • Governance-at-the-data-layer is still in preview (GA expected H2 2026)
  • Performance multiples (10x/8x) are vendor-reported

Pricing

EDB Postgres AI

Contact for pricing

  • Predictable per-core pricing
  • On-premises, hybrid, and bring-your-own-cloud (BYOC) options
  • EDB Developer Cloud

EDB references predictable per-core pricing and offers bring-your-own-cloud (BYOC) and an EDB Developer Cloud; detailed list pricing is not published in the announcement.

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EDB Postgres AI (EDB PG AI) is a sovereign data-and-AI platform built on open-source PostgreSQL that unifies transactional, analytical, vector, and agentic workloads through a single SQL interface. It is aimed at CIOs, CTOs, and data leaders who need AI-ready infrastructure without moving data into a separate cloud or vector store.

At a Glance

Category
Data & Analytics
Pricing
Subscription, Contact for pricing
Target Market
CIOs, CTOs, Data Engineers, Database Administrators, Enterprise Architects
Founded
2004
Headquarters
Wilmington, Delaware, USA

Key Features

  • Agentic database

    A self-optimizing system that monitors 200+ metrics and automates tuning, with EDB citing up to 10x faster tuning and up to 8x faster application performance.

  • Converged analytics

    A zero-ETL architecture that publishes operational data to Apache Iceberg and adds ClickHouse and WarehousePG for real-time to petabyte-scale analytics.

  • Native vector search

    A unified query layer over vector, structured, and unstructured data so agents retrieve context they are authorized to access without a separate vector store.

  • Governance at the data layer

    Row-level and role-based access enforced in the moment of action, giving every agent a declared owner and boundary (in preview, GA expected H2 2026).

  • Sovereign, open-source Postgres foundation

    Built on open-source PostgreSQL and deployable on-premises, hybrid, or across multiple clouds to preserve data sovereignty.

Capabilities

text generation
image generation
video generation
code generation
workflow automation
api access
audio generation
fine tuning
agent orchestration

Use Cases

  • Unify AI and operational data

    Serve relational, JSON, time-series, geospatial, and vector data through a single SQL interface for AI applications.

  • Reduce database sprawl

    Consolidate transactional, analytical, and vector workloads onto one governed Postgres platform instead of many specialized stores.

  • Ground enterprise AI agents

    Give agents accurate, authorized retrieval on live data with governance enforced at the row level.

Ideal For

Best For

  • Running relational, analytical, vector, and agentic workloads on one Postgres foundation
  • Sovereign and on-premises AI where data cannot leave the enterprise
  • Giving AI agents governed, authorized retrieval without a separate vector database

Integrations

SDK Available
SDK:PythonSQL

Deployment

On-Premise

Market Analysis

Enterprise-gradeSovereign AI operating system for the agentic era

Pros

  • Built on open-source PostgreSQL for portability and sovereignty
  • Removes the need for a separate vector store
  • Strong hardware and platform partner ecosystem

Cons

  • Governance-at-the-data-layer is still in preview (GA expected H2 2026)
  • Performance multiples (10x/8x) are vendor-reported

Pricing

Free Trial Available

EDB Postgres AI

Contact for pricing

  • Predictable per-core pricing
  • On-premises, hybrid, and bring-your-own-cloud (BYOC) options
  • EDB Developer Cloud

EDB references predictable per-core pricing and offers bring-your-own-cloud (BYOC) and an EDB Developer Cloud; detailed list pricing is not published in the announcement.

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