Databricks, the Data and AI company, has introduced Lakebase, a groundbreaking, fully-managed Postgres database purpose-built for artificial intelligence. This launch marks a strategic expansion of the Databricks Data Intelligence Platform, bringing an operational database layer into the fold. With Lakebase, developers and enterprises can now streamline the creation of data applications and AI agents, all within a unified, multi-cloud ecosystem. The service is currently available in Public Preview.
Operational databases—forming the backbone of every digital application—represent a market exceeding $100 billion. Yet, the foundational architecture of these systems hasn’t kept pace with modern demands. Legacy OLTP databases are often complex to maintain, costly, and susceptible to vendor lock-in. As AI continues to drive a new wave of intelligent applications and automation, there is a pressing need for systems that can provide real-time, reliable data at the speed required by AI agents.
Lakebase is engineered to meet these demands by bridging operational and analytical workloads. Built on Neon technology, it brings operational data directly into the lakehouse, utilizing cost-efficient data lakes while dynamically autoscaling compute resources to support fluctuating agent workloads. The platform enables developers to build, test, and deploy intelligent applications more efficiently and at scale.
“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 As AI agents reshape how businesses operate, Fortune 500 companies are ready to replace outdated systems.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.”
Also Read: AWS Launches Amazon Aurora DSQL, Fastest Distributed DB
Key Features of Lakebase:
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Separation of Compute and Storage: Lakebase leverages Neon’s cloud-native architecture with decoupled compute and storage, ensuring high performance with sub-10ms latency, support for over 10K QPS, and high availability for transactional workloads.
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Open-Source Foundation: As a Postgres-compatible system, Lakebase taps into the power of a vast open-source ecosystem. It supports seamless integration with community tools and LLM-based agent workflows, which are often trained on Postgres datasets.
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AI-Optimized Development: Developers can spin up instances in under a second and benefit from pay-as-you-go pricing. The branching feature enables safe testing and experimentation through copy-on-write database clones.
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Deep Lakehouse Integration: Lakebase ensures bi-directional sync with lakehouse tables, provides an online feature store for real-time model serving, and integrates with Unity Catalog and Databricks Apps.
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Enterprise-Grade Security and Management: As a fully managed solution, Lakebase offers hardened infrastructure, end-to-end encryption, point-in-time recovery, and enterprise controls for security, compliance, and network governance.
Industry Adoption and Use Cases
Lakebase is already gaining traction across industries, with hundreds of enterprises participating in its Private Preview. From real-time personalization and agent-driven e-commerce to clinical trial management, organizations are leveraging the unified platform for intelligent, low-latency applications.
“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.” — Jelle Van Etten, Head of Global Data Platform at Heineken
“Lakebase removes the operational burden of managing transactional databases. Our customers can focus on building applications instead of worrying about provisioning, tuning and scaling.” — Anjan Kundavaram, Chief Product Officer at Fivetran
“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 maximize the value they derive across their entire data estate — from storage to AI-enabled application deployment.” — David Menninger, Executive Director, ISG Software Research