EnterpriseDB (EDB), a prominent player in the realm of sovereign AI and data solutions, has unveiled significant advancements in its integration with NVIDIA’s cuDF for Apache Spark. This collaboration aims to enhance Postgres® performance on NVIDIA AI infrastructure, promising enterprises a remarkable leap in analytics capabilities—up to 100 times faster than traditional methods. Such improvements are crucial as organizations strive to scale their agentic workforce on a robust AI foundation.
Transforming Data Architecture
As the era of the agentic workforce unfolds, autonomous agents are emerging as the primary consumers of enterprise data. These intelligent systems require the ability to reason, collaborate, and act on vast amounts of real-time information. However, many organizations find themselves hindered by fragmented data silos and inefficient analytics processes, leading to increased governance and operational risks.
To address these challenges, EDB emphasizes the necessity of a real-time analytics framework that is not only fast and predictable but also designed with sovereignty in mind. The integration of GPU acceleration with cuDF for Apache Spark provides a unified platform that meets these demands.
“The arrival of the agentic workforce demands a rethink of data architecture. To stay relevant, enterprises need to reduce the ‘data ping-pong’ across fragmented platforms that can stall progress,” stated Devin Pratt, research director at IDC. “EDB Postgres AI, powered by NVIDIA AI and accelerated computing, is positioned as the high-velocity, enterprise-ready foundation for operating these agentic systems at scale.”
Capabilities of EDB Postgres AI
The enhanced functionalities of EDB Postgres AI (EDB PG AI) are tailored for secure enterprise operations, allowing organizations to transition from isolated experiments to systems of autonomous agents capable of processing billions of records in real-time. Key features include:
- GPU-acceleration: Interactive analytics on Postgres data through a single interface, featuring Apache Iceberg integration for secure zero-ETL data replication to lakehouses.
- NVIDIA NIM model serving: Optimized on-premises inference for models like NVIDIA Nemotron.
- Fully air-gapped support: Capability to import containers and models into private registries and storage.
- High-speed RAG: Accelerated with NVIDIA NeMo Retriever.
From Experimentation to Deployment
As enterprises evolve from generative AI pilots to fully operational agentic workforces, the underlying data infrastructure becomes pivotal. EDB’s research indicates that only 13% of enterprises have successfully transitioned to production-scale agentic deployments with over ten active workflows. These organizations report five times higher ROI compared to their peers and operate with double the density of agents per business process.
Agentic systems increasingly require the ability to reason with live enterprise data in real-time while also leveraging transactional records and historical context. This capability allows agents to process terabytes of data in seconds, facilitating conversational analytics, real-time decision-making, and multi-agent orchestration without incurring excessive costs or duplicating data across warehouses and lakes.
Through its integration with Apache Spark, accelerated by NVIDIA cuDF, the EDB PG AI Analytics Engine offloads analytical workloads to GPUs, achieving:
- 50–100x faster, predictable analytics on large datasets (3TB+).
- GPU-based workload isolation to safeguard query performance.
- Support for lakehouse architectures and governance capabilities via Apache Iceberg.
- Enterprise-grade and sovereign by design.
“Enterprises want GPU acceleration, but they also need predictability and control. NVIDIA cuDF for Apache Spark with Apache Iceberg support allows us to offload heavy analytics to GPUs while EDB PG AI ensures workload isolation, governance, and a consistent operational model. This distinction is what separates impressive demonstrations from sustainable production systems,” remarked Quais Taraki, CTO of EDB.
As part of its commitment to education, every attendee at NVIDIA GTC 2026 will receive a complimentary hard copy of EDB’s pioneering book, Building a Data and AI Platform with PostgreSQL.
For further insights and access to the complete benchmark report, visit the webpage here.
About EDB
EDB Postgres® AI (EDB PG AI) stands as the first open, enterprise-grade sovereign data and AI platform—secure, compliant, and scalable, whether on-premises or across clouds. Built on Postgres, the world’s leading database, EDB PG AI integrates transactional, analytical, and AI workloads, empowering organizations to operationalize their data and large language models while maintaining control over their sovereign environments. Supported by a global partner network, EDB PG AI offers up to 99.999% availability alongside hybrid management and an integrated AI factory. As a key contributor to the PostgreSQL project, EDB is dedicated to fostering the health of the global community. To learn more, visit www.enterprisedb.com.
Media contact:
Steph McGuirk
Interdependence
(845) 269-8868
[email protected]
EnterpriseDB and EDB are registered trademarks of EnterpriseDB Corporation. Postgres and PostgreSQL are registered trademarks of the PostgreSQL Community Association of Canada and used with their permission. All other trademarks are owned by their respective owners.
