This blog was co-authored by Jack Christie and Dave Stone.
EDB Postgres AI Analytics Accelerator breaks down data silos by turning your sovereign Postgres environment into a powerful analytics hub.
We’re excited to announce general availability of EDB Postgres AI Analytics Accelerator, our suite of analytics capabilities that includes an engine for rapid analytics across Postgres and the lakehouse ecosystem, and WarehousePG, a powerful new open-source data warehouse offering. Read on for more details about how this solution meets today’s enterprise needs.
The high cost of data complexity
Every business wants to be data-driven, and you’d think it would get easier with the ever-increasing volume and variety of data — but enterprises know firsthand that the opposite is true. The constant influx of structured, semi-structured, and unstructured data across siloed sources makes it hard to find any signal in the noise. In fact, data silos cost businesses an average of $3.1 trillion annually in lost revenue and productivity, explaining why eight out of ten business decision-makers cite reducing data and information silos as a top priority.
Typically, enterprises have two options to tackle this problem. Some businesses look to consolidate transactional and analytical workloads in a single data store like Postgres, but historically, that has come with slower, row-based querying and resource bottlenecks for compute and storage that disrupt business continuity. Other businesses who don’t like those downsides choose instead to invest in separate transactional and analytical systems, but this fragmented approach requires complex maintenance and can actually exacerbate silos. Specialized analytical stores are often proprietary, too, which further amplifies challenges by restricting flexibility, increasing costs, and impeding the adoption of modern data strategies.
How can enterprises minimize these tradeoffs and unlock the data- and AI-driven future?
Introducing Analytics Accelerator: Get better, faster analytics with sovereign control and take action through agentic analytics
EDB Postgres AI Analytics Accelerator, now generally available, turns Postgres into a columnar analytics database with lakehouse integration. Now, you can make decisions more efficiently with 30x faster insights from your operational data, while protecting business continuity with dedicated analytics compute resources and automatic storage optimization.
By enabling queries and governance across the modern lakehouse ecosystem from your sovereign, secure Postgres foundation, Analytics Accelerator eliminates data silos and future-proofs your data strategy — giving you the flexibility to adapt to the latest technologies, like combining artificial intelligence and business intelligence (AI-BI) in powerful analytics agents.
Key features
Analytics Accelerator is powered by a specialized engine that drives rapid insights across siloed data, lakehouse interoperability and automatic storage optimization, and open ecosystem integrations that ensure you can modernize to new analytics paradigms and maximize the value of your data:
- Analytics Engine: Query data 30x faster, on average, than standard Postgres while eliminating extract, transform, and load (ETL) pipelines with a vectorized engine optimized for querying columnar data formats Apache Iceberg and Delta Lake from Postgres.
- Lakehouse Connector: Manage queries and governance across the lakehouse ecosystem — including Databricks and Snowflake — from your sovereign Postgres environment. Optimize costs and performance by automatically offloading cold transactional data to lakehouse tables in economical storage for 18x cost savings.
- WarehousePG: Modernize Greenplum data warehouses with 24x7 support and secure distribution of WarehousePG, an Apache-licensed drop-in replacement that lets you reclaim open source innovation without new skills or infrastructure.
Key benefits
EDB Postgres AI Analytics Accelerator provides game-changing benefits for enterprises dealing with the pain of data complexity and the pressure to modernize. Not only do businesses get faster revenue-driving insights from operational data while removing data silos and ETL pipelines; they also get upgraded availability for both their data teams and infrastructure.
By simplifying data management in familiar Postgres, data teams get time back to focus on higher-value tasks — and high availability, automatic storage optimization, and separation of storage and compute ensure your business stays up and running. Plus, you can pursue modernization with lakehouse interoperability while maintaining strict governance in your sovereign, secure Postgres environment.
When you combine these open ecosystem integrations with EDB Postgres AI Factory, our end-to-end GenAI inference platform, you have everything you need to bridge the gap between legacy and next-gen systems with cutting-edge analytics agents.
Take a look at this demo to see Analytics Accelerator in action.
Getting practical: How Analytics Accelerator empowers your use cases, our customers, and our own organization
Cutting-edge use cases
Now that we’ve explored the core capabilities and benefits of Analytics Accelerator, let’s look at what this platform actually enables for businesses like yours. We’re excited to see customers leveraging a unified platform for analytics to solve complex challenges and drive innovation for success in the AI generation.
Unified Query Engine
EDB Postgres AI addresses the complexity of managing multiple query engines across analytics, AI, and transactional workloads. Rather than maintaining separate systems with governance challenges and legacy silos, EDB Postgres AI transforms Postgres into a trusted, sovereign engine for search across Postgres, the lakehouse, and anywhere else your data lives. This provides one platform for querying all data with real-time processing capabilities, while improving efficiency, flexibility, scalability, and security. Organizations eliminate the fragmentation of too many specialized systems while gaining the performance benefits of 30x faster queries compared to standard Postgres.
Agentic Analytics
EDB Postgres AI changes how teams interact with data by combining Analytics Accelerator and AI Factory capabilities to deploy intelligent agents that analyze and take action in real-time. Unlike traditional approaches that require manual queries, static dashboards, and human-dependent decision making, agentic analytics pulls together data from different locations — including Iceberg and Delta tables through our Lakehouse Connector — and enables autonomous monitoring with 24x7 intelligent responses. The result is faster lead discovery, reduced manual effort, and higher conversion rates as agents continuously optimize based on real-time insights across your entire data ecosystem.
Dive deeper into agentic analytics and how EDB Postgres AI makes it possible.
Dynamic Analytics
EDB Postgres AI eliminates the cost-performance tradeoffs associated with combining real-time and historical data. Typically, the costly storage bloat of keeping everything in a single transactional system isn’t worth the short-term query performance improvements — but separating data across different systems, while potentially more cost-efficient, comes with its own complexity and latency implications. With tiered tables from EDB Postgres AI Analytics Accelerator, cold data is automatically offloaded from Postgres to lakehouse tables in cost-efficient object storage, while the Analytics Engine enables seamless SQL querying across storage tiers. This streamlined approach simplifies management and boosts performance while protecting business continuity for always-on systems.
Read more about powering dynamic analytics with EDB Postgres AI.
Proven results from our customers
We're already seeing global organizations like our own harness EDB Postgres AI Analytics Accelerator to improve performance, streamline operations, and modernize systems.
Euronext FX reclaims open source flexibility while preserving existing investments
Euronext FX, a major European market infrastructure, faced significant limitations with its closed source Greenplum system. EDB Postgres AI provided a solution by enabling a seamless transition to Greenplum-compatible, open source WarehousePG and a path to version upgrades for further modernization.
“We’re excited to be working with EDB Postgres AI. Its Support for Greenplum Workloads is helping us maintain control of where and how we deploy open source software.”
— Grigoriy Zeleniy, Global CTO at Euronext FX
EDB eliminates data silos with lakehouse modernization
We ourselves are familiar with the pain of data silos hindering unified reporting and timely decision-making. EDB’s own Data, Analytics, and AI team overcame this by implementing Mission Control, a centralized dashboard system built on EDB Postgres AI. They leveraged Analytics Accelerator lakehouse integrations to consolidate data from various departments into a single source of truth and empower rapid insights across the organization. This transformation has reduced query runtimes by 50-90%, enhanced our operational efficiency, and empowered our teams to make strategic decisions with greater confidence and precision.
“EDB Postgres AI has turbocharged our data warehouse, slashing query runtimes by 50-90%."
— Dan Merzlyak, SVP, Global Head of Data, Analytics, and AI at EDB
Read more of the story on the EDB blog.
Ready to innovate with EDB Postgres AI?
The future of enterprise data lies in converging analytical, transactional, and AI workloads, and EDB Postgres AI is leading the way as the sovereign Postgres platform built to address this demand. For a comprehensive look at our latest advancements, be sure to read our main Q2 release blog, and check out our demos page to see EDB Postgres AI in action. If you want to learn more, reach out to schedule a comprehensive demo and expert consultation for your use cases.
Disclaimer: Greenplum® is a registered trademark of Broadcom Inc. EDB and EDB Postgres AI are not affiliated with, endorsed by, or sponsored by Broadcom Inc. Any references to Greenplum are for comparative, educational, and interoperability purposes only.