EnterpriseDB, a prominent player in the Postgres data and AI landscape, has unveiled significant advancements to its EDB Postgres AI (EDB PG AI) platform. These innovations are crafted to empower enterprises in deploying and scaling AI solutions securely and in compliance with regulations across their Postgres environments, whether hosted in the cloud or on-premises. The platform enhances operational efficiency at scale, integrates seamlessly with existing data ecosystems, and centralizes hybrid management and observability within a single AI-ready control plane, catering to the evolving needs of agentic AI.
Unified Platform for Diverse Workloads
EDB PG AI stands out as a unified platform featuring an intuitive interface for managing transactional, analytical, and AI workloads. As the first Postgres-based sovereign data and AI platform in the industry, it consolidates both relational and non-relational data into a single system. The platform boasts automatic pipelines and built-in development tools that facilitate the seamless automation and operationalization of data for AI applications.
Kevin Dallas, CEO of EDB, emphasized the pressing demand from C-suite executives worldwide for a secure, open-source, sovereign data and AI platform that grants them full control over their AI development. He stated, “True data and AI sovereignty means we are giving enterprises the freedom to choose—hybrid, with unique engineered systems, software, and cloud offerings—while also ensuring that they have the security and control they need.”
According to EDB research conducted in May 2025, only 13% of enterprises globally have successfully implemented a wide array of agentic AI applications at scale. Those early adopters are witnessing remarkable returns, achieving up to 227% higher ROI compared to the remaining 87%, and 23% better ROI than the next-best group.
Stefanie Chiras, Senior Vice President of Partner Ecosystem Success at Red Hat, noted the growing trend among customers to adopt tested, optimized, and scalable architectures for implementing open-source AI at the enterprise level. She highlighted the collaboration between Red Hat and EDB, which aims to provide organizations with the necessary solutions, services, and support to achieve successful AI outcomes. By utilizing EDB Postgres AI alongside Red Hat OpenShift AI, organizations can establish a more consistent platform for sovereign control over their data and AI models.
New Core Capabilities
The latest iteration of the EDB PG AI platform introduces two pivotal capabilities designed to enable secure, scalable, and hybrid-ready agentic AI, making production-grade performance accessible to enterprises managing their Postgres environments:
- Low-code/no-code simplicity: AI pipeline creation in days, not months
The platform allows developers and business users to construct intelligent applications through a user-friendly point-and-click interface and low-code software development kit (SDK). This capability transforms GenAI projects from concept to production in a matter of days rather than months, all within a pre-integrated platform. Users can establish an AI pipeline with just five lines of code, ensuring that their AI knowledge base remains current without incurring costly infrastructure maintenance. The integration of NVIDIA accelerated computing provides the necessary processing performance for this new paradigm, while NVIDIA NIM microservices enable enterprises to run AI models locally, safeguarding their data with sovereign AI.
These features collectively empower enterprises to operationalize their AI securely, at scale, and on their preferred infrastructure.
- Sovereign hybrid Postgres data estate management and observability
The hybrid management feature offers comprehensive visibility across the entire Postgres estate, equipping developers and operators with real-time insights across numerous databases via an intuitive interface. With over 200 built-in metrics and intelligent recommendations, teams can identify and resolve issues five times faster, enhance application performance by up to eight times, and optimize infrastructure—all without requiring DBA expertise. This ease of management can boost productivity by as much as 30% while reducing total cost of ownership (TCO) by up to six times compared to legacy systems.
Cenly Chen, Chief Growth Officer at Supermicro, remarked on the collaborative efforts behind the EDB Postgres AI engineered solution, which leverages Supermicro’s strengths in data center systems and rack-scale AI solutions. This unified offering provides full hybrid capabilities, enabling customers to construct sovereign, scalable, and compliant data and AI systems.
Additional Enhancements
Further enhancements to the platform include:
- Data security at all layers with Transparent Data Encryption (TDE), supply chain security, and hardened container images from Iron Bank. Advanced security features encompass role-based access control with fine-grained permissions, robust audit logging for real-time threat detection, and data redaction to limit sensitive information exposure, ensuring compliance with evolving regulations such as PCI DSS and SOC 2.
- Purpose-built PG AI Analytics Engine that scales independently from storage and is optimized for columnar formats like Iceberg and Delta tables. This engine drives high-performance queries across Postgres and the lakehouse ecosystem, enabling enterprises to unlock insights 30 times faster than standard Postgres by utilizing fresh operational data and eliminating ETL pipelines.
- A universal, secure data store that accommodates all data models—SQL, vector, JSON, time-series, key-value, and more—allowing for the development of applications with structured, semi-structured, and unstructured data types. The tiered storage and query engine unify Postgres with scalable analytics tables in object storage, delivering optimized read/write performance that scales seamlessly from high-concurrency transactions to complex analytical and vector queries.
Performance advantages include:
- Six times better TCO and 30% faster transactional performance than SQL Server
- Up to 150 times faster NoSQL performance compared to MongoDB
- Up to four times faster NoSQL performance compared to MySQL
William McKnight, President of McKnight Consulting Group, shared insights from a comparative analysis of the integrated EDB Postgres AI platform against a typical DIY approach using AWS. The findings revealed that EDB Postgres AI reduced overall complexity by 67%, achieved a threefold increase in design-to-delivery capability (from seven months to nine weeks), and resulted in a 38% reduction in maintenance complexity and costs.
EDB PG AI signifies a pivotal moment for enterprises aiming to leverage the full potential of their data in the age of agentic AI.
