Databricks launches Lakebase Postgres database for AI era
Databricks has launched Lakebase, a fully managed Postgres database designed specifically for artificial intelligence (AI) applications, and made it available in Public Preview.
Lakebase integrates an operational database layer into Databricks' Data Intelligence Platform, with the goal of enabling developers and enterprises to build data applications and AI agents more efficiently on a single multi-cloud environment.
Purpose-built for AI workloads
Operational databases, commonly known as Online Transaction Processing (OLTP) systems, are fundamental to application development across industries. The market for these databases is estimated at over USD $100 billion. However, many OLTP systems are based on architectures developed decades ago, which makes them challenging to manage, inflexible, and expensive. The current shift towards AI-driven applications has introduced new technical requirements, including the need for real-time data handling and scalable architecture that supports AI workloads at speed and scale.
Lakebase, which leverages Neon technology, delivers operational data to the lakehouse architecture — combining low-cost data storage with computing resources that automatically scale to meet workload requirements. This design allows for the convergence of operational and analytical systems, reducing latency for AI processes and offering enterprises current data for real-time decision-making. "We've spent the past few years helping enterprises build AI apps and agents that can reason on their proprietary data with the Databricks Data Intelligence Platform," said Ali Ghodsi, Co-founder and CEO of Databricks. "Now, with Lakebase, we're creating a new category in the database market: a modern Postgres database, deeply integrated with the lakehouse and today's development stacks. As AI agents reshape how businesses operate, Fortune 500 companies are ready to replace outdated systems. With Lakebase, we're giving them a database built for the demands of the AI era."
Key features
Lakebase separates compute and storage, supporting independent scaling for diverse workloads. Its cloud-native architecture offers low latency (under 10 milliseconds), high concurrency (over 10,000 queries per second), and is designed for high-availability transactional operations. The service is built on Postgres, an open source database engine widely used by developers and supported by a rich ecosystem.
For AI workloads, Lakebase launches in under a second and operates on a consumption-based payment model, so users only pay for the resources they use. Branching capabilities allow developers to create copy-on-write database clones, supporting safe testing and experimentation by both humans and AI agents.
Lakebase automatically syncs data with lakehouse tables and provides an online feature store for machine learning model serving. It also integrates with other Databricks services, including Databricks Apps and Unity Catalog. The database is managed entirely by Databricks, with features such as encrypted data at rest, high availability, point-in-time recovery, and enterprise-grade compliance and security.
Market adoption and customer perspectives
According to the company, hundreds of enterprises participated in the Private Preview stage of Lakebase. Potential applications for the technology span sectors, from personalised product recommendations in retail to clinical trial workflow management in healthcare.
Jelle Van Etten, Head of Global Data Platform at Heineken, commented: "At Heineken, our goal is to become the best-connected brewer. To do that, we needed a way to unify all of our datasets to accelerate the path from data to value. Databricks has long been our foundation for analytics, creating insights such as product recommendations and supply chain enhancements. Our analytical data platform is now evolving to be an operational AI data platform and needs to deliver those insights to applications at low latency."
Anjan Kundavaram, Chief Product Officer at Fivetran, said: "Lakebase removes the operational burden of managing transactional databases. Our customers can focus on building applications instead of worrying about provisioning, tuning and scaling."
David Menninger, Executive Director at ISG Software Research, said: "Our research shows that the data and insights from analytical processes are the most critical data to enterprises' success. In order to act on that information, they must be able to incorporate it into operational processes via their business applications. These two worlds are no longer separate. By offering a Postgres-compatible, lakehouse-integrated system designed specifically for AI-native and analytical workloads, Databricks is giving customers a unified, developer-friendly stack that reduces complexity and accelerates innovation. This combination will help enterprises maximise the value they derive across their entire data estate — from storage to AI-enabled application deployment."
Integration and partner network
Lakebase is launching with support from a network of partners, including technology vendors and system integrators such as Accenture, Deloitte, Cloudflare, Informatica, Qlik, and Redis, among others. These partnerships are designed to ease data integration, enhance business intelligence, and support governance for customers as they adopt Lakebase as part of their operational infrastructure.
Lakebase is now available in Public Preview with further enhancements planned in the coming months. Customers can access the preview directly through their Databricks workspace.
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