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title: Introducing Lakebase: A New Era in Database Architecture
description: Databricks launched Lakebase, a fully-managed serverless PostgreSQL database that integrates with their lakehouse architecture. Built on Neon technology, it...
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# Introducing Lakebase: A New Era in Database Architecture

**[Collections](https://daily.dev/sources/collections)** · 2 min read · 1 upvotes · 0 comments

## Summary

Databricks launched Lakebase, a fully-managed serverless PostgreSQL database that integrates with their lakehouse architecture. Built on Neon technology, it features automatic scaling, instant database branching, Unity Catalog integration, and AI-agent optimization. The platform separates storage and compute for independent scalability while maintaining high concurrency and low latency. Lakebase is currently in public preview and designed specifically for AI-driven applications and machine learning workloads.

## Content

# Databricks' Lakebase: A Managed PostgreSQL Solution for the AI Era

Databricks has introduced several innovative AI-focused products at its recent user conference, emphasizing its commitment to evolving data management and analytics for modern applications. A cornerstone of these announcements is Lakebase, a fully-managed, serverless PostgreSQL database built leveraging technology from Databricks' Neon acquisition.

## Lakebase: A New Era for PostgreSQL

Lakebase harnesses the familiarity and robustness of PostgreSQL while integrating it with Databricks' cutting-edge lakehouse architecture. This integration offers seamless scalability through serverless auto-scaling and separates storage and compute layers, a design that allows for independent scalability while ensuring high concurrency and low latency.

### Key Features

- **Serverless Autoscaling**: Built on Neon technology, Lakebase ensures resources are allocated dynamically based on demand, optimizing cost efficiency and performance without manual oversight.

- **Instant Database Branching**: The copy-on-write branching capability facilitates rapid configuration and development workflows, enabling developers to test and iterate quickly.

- **Integration with Unity Catalog**: This alignment provides a unified interface to manage both operational and analytical data, enhancing data governance and ease of use.

- **AI-Agent Friendly**: With 80% of Neon databases created by AI agents, Lakebase serves as a robust platform for AI applications, including serving as an online feature store for machine learning models.

## Enhanced AI Ecosystem

In addition to Lakebase, Databricks revealed other products designed to bolster AI infrastructure and accessibility. Notable among these is Agent Bricks, a platform for developing AI agents tailored to specific tasks and functionalities. Complementing this, the Lakeflow Designer offers a no-code pipeline builder to streamline ETL processes via its newly open-sourced Apache Spark Declarative Pipelines framework.

Databricks has also enriched its ecosystem with features targeting business users, such as AI/BI Genie, allowing natural language interactions with data, and Databricks One, which simplifies navigation for non-technical users.

## Public Preview Announcement

Lakebase is currently in public preview, inviting users to explore and leverage its capabilities for AI-driven applications. Users can anticipate remarkable provisions such as automatic scaling and minimized infrastructure management overhead, streamlining the operational demands and broadening accessibility.

In summary, Databricks with Lakebase is set to redefine database management by merging classical PostgreSQL architectures with modern demands for flexibility, scalability, and AI integration. As it moves into public preview, Lakebase presents a compelling option for organizations seeking to leverage AI in their data operations efficiently.

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---

Tags: [#postgresql](https://daily.dev/tags/postgresql), [#serverless](https://daily.dev/tags/serverless), [#databricks](https://daily.dev/tags/databricks)

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