EDB Postgres AI

EDB Postgres AI is a single platform for transactional, analytical and AI workloads, built on the Postgres database engine. It's intended to unify different data management tasks, including analytics and AI, into one platform. EDB Postgres AI is an enterprise-grade Postgres database extension with native AI vector processing, an analytics lakehouse, and unified observability and hybrid data management.

EDB Postgres AI includes a number of features:

• Native AI Vector Processing: Runs AI applications with a single data layer and offers a full set of tools for AI developers.
• Analytics Lakehouse: Supports modern lakehouse projects, combining data from Postgres and outside sources without creating new data silos.
• Unified Observability: Offers a single window into the world of hybrid data estates to ensure business continuity, security and compliance.
• AI-Driven Copilots and Automation: Offers solutions for non-expert users to apply AI to different workloads.
• High Availability and Performance: Offers up to 99.999% availability and up to 5X throughput performance compared to vanilla Postgres.
• Comprehensive Migration Tooling: Makes it easy to move from legacy systems, including Oracle compatibility.

EDB Postgres AI can be used for a variety of workloads:

• Transactional Workloads: Gives enterprise developers a flexible and extensible general-purpose database.
• Analytical Workloads: Supports strategic analytics and data science projects without requiring a separate data platform.
• AI Workloads: Supports transformative AI workloads with enterprise-grade security and scalability.

EDB Postgres AI can be deployed in a variety of ways, including cloud-managed services, self-managed software and physical appliances. That flexibility means customers can pick the best option for their needs, whether that's in a hybrid or multi-cloud environment.

EDB Postgres AI is designed to make data infrastructure a strategic technology asset, making it a good option for companies that want to add AI and analytics to their Postgres-based workloads.

Published on June 25, 2024