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Databricks

How lakebase architecture delivers 5x faster Postgres writes Why Talent Transformation Is the Missing Focus of Enterprise AI Public Health Intelligence Shouldn't Require a Data Scientist Mean Time to Detect Is a Data Access Problem First-party audience data is the ad sales relationship now Rethinking Distributed Systems for Serverless Performance and Reliability The AI Scaling Gap Hiding in Digital Native Companies 10 trillion samples a day: Scaling beyond traditional monitoring infra at Databricks AI success starts with clean data, not just better models How nOps Rebuilt Their Cloud Optimization Platform on Databricks Lakebase, and Why Other ISVs Should Too Peril Predicts: Precision Payouts for a Volatile World The foundation of AI scalability: one team, one platform, one operating model The Federal Data Paradox: Rich in Data, Poor in Access Driving Budapest Forward: How BKK Uses Databricks to Transform City Mobility LLM Vs AI: A Practical Guide to Differences, Use Cases, and Tools Model Risk Governance Is Not the Same as Risk Intelligence Generative AI for Business: A Complete Strategy and Implementation Guide Data Science vs Data Engineering: Choosing Analysis or Infrastructure AI Applications: Tools, Use Cases, and Platforms MLOps vs DevOps: A Practical Guide for Data Scientists and IT Teams Top Data Warehouse Tools For Modern Data Analytics Unlocking SAP Business Context in Databricks with Semantic Metadata Delta Sharing The marketing activation gap has a fix: Databricks and Stitch partner to turn data infrastructure into marketing performance Alert Fatigue Is a Business Risk Backstage with Lakebase Shipping Faster isn’t Learning Faster Why Your OEE Dashboard Is Lying to You The Turbine That Tried to Tell You It Was Failing Predicting Readmissions Isn't Enough. Acting in Time Is. Clinical Trials Run Longer Than They Have To. That's a Patient Problem Network Quality Is a Revenue Problem, Not a Technical One Shelf Availability Starts with Better Demand Visibility When Predicting the Next Hit Requires More Than Intuition Approximate Answers, Exact Decisions: New Sketch Functions for Analytics Companies Winning with AI Built the Data Layer First Rethinking SQL ETL for modern data platforms Stripe data now available on Databricks via Databricks Marketplace Agents are ready but your architecture probably isn't Interoperability Between Unity Catalog and Google BigQuery via Catalog Federation Built In, Not Bolted On: What AI-Native Actually Means in Cybersecurity Operationalizing AI for public sector fraud prevention From months to minutes: Building real-time clinical data pipelines with natural language Agentic Data Engineering with Genie Code and Lakeflow Securely send first-party conversion signals with Snapchat Conversions API on Databricks Marketplace How leading tech companies are killing the builder’s tax with Lakebase Inside one of the first production deployments of Lakebase: LangGuard's agentic workflow governance engine The next generation of Databricks Genie Model Risk Management in 2026: A Banker’s Guide to the Revised Interagency Guidance OpenAI GPT-5.5 now available on Databricks, fully-governed through Unity AI Gateway Operational databases: How they work and when to use them Databricks partners with OpenAI on GPT-5.5 Announcing the Public Preview of Lakeflow Designer Are LLM agents good at join order optimization? How conversational analytics removes the BI bottleneck How to transform document activation workflows with Genie and Agent Bricks Beyond the spreadsheet: how Databricks is delivering the modern CFO in Financial Services AI App Development: Guide To Building AI-Powered Apps IoT in Manufacturing: Strategy, Components, Use Cases, and Challenges Stop Hand-Coding Change Data Capture Pipelines Multimodal Data Integration: Production Architectures for Healthcare AI Personalization Strategies for Media Companies A Modern AI Risk Management Framework Introducing the Databricks Excel Add-in for Business Users Real-Time Decisioning for AI Agents: Why you Need a Customer Context Layer First A Practical Guide to LLM Fine Tuning AI Data Transformation Guide for Data Engineers and Data Scientists Concurrency Control in DBMS: How Locking, MVCC and Optimistic Strategies Keep Data Consistent Bridging data science and marketing: Databricks unveils Delta Sharing integration for Adobe Experience Platform and agentic marketing workflows Take Control: Customer-Managed Keys for Lakebase Postgres Get hands on with agents, vibe coding and more at Data+ AI Summit Mercedes-Benz Builds a Cross-Cloud Data Mesh with Delta Sharing and Intelligent Replication, Cutting Costs by 66% What Is a Transactional Database? 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Databricks and Stripe Projects: Infrastructure Built for Agents
2026-04-29 · via Databricks

Databricks is a launch partner for Stripe Projects, the new tool that lets AI agents provision production-ready Neon Postgres without human interaction.

by Brad Van Vugt and Guillaume Rivals

AI coding agents can create, scaffold, and deploy a full-stack app in minutes. But provisioning application infrastructure still requires human effort and can slow you down significantly.

Humans are still required to provision services, navigate UIs, configure accounts, enter credit card info, etc. Every manual step is one where autonomous app development fails - manual provisioning is no longer just a friction point, but a clear gap in AI app development.

Databricks has partnered with Stripe Projects to close that gap. 

Introducing agentic provisioning of Neon databases using Stripe Projects. 

Today Stripe is launching Stripe Projects - a new agent-first CLI tool that allows AI agents to discover, provision, and pay for Neon databases. It’s the first fully-agentic provisioning tool of its kind.

Databricks is a proud launch partner, bringing Neon databases seamlessly to every AI development environment. Agents can now get a production-ready Neon Postgres database in under 350ms, without any human interaction.

Lakebase and Neon: a foundation for autonomous infrastructure

To allow AI agents to manage infrastructure independently, the underlying database must be as flexible and programmable as the agent itself. Lakebase architecture, developed by Neon, is the first serverless Postgres database designed for the AI era. By decoupling compute from storage, agents can create, build, and tear down OLTP databases in seconds.

This agent-first architecture is built on three core technical pillars:

  • Serverless Scaling and Scale-to-Zero: Traditional databases require manual provisioning and "always-on" costs. Lakebase compute resources dynamically adjust to match traffic spikes in real-time and automatically scale to zero when idle. For agents, this means they can spin up production-ready environments without worrying about capacity planning or wasted spend.
  • Instant Database Branching: Using zero-copy cloning, agents can create isolated branches of production data in seconds. This allows autonomous systems to safely test code, run migrations, or experiment with new prompts against live data states without risking the primary production environment or incurring massive storage overhead.
  • It’s Postgres: Agents understand Postgres better than any other OLTP database, meaning that software development using the Lakebase architecture is quick and easily automated.

By treating the database as a programmable, on-demand service rather than a static piece of hardware, lakebase architecture allows agents to bridge the gap between scaffolding an idea app and running a production application.

Getting started with Neon and Stripe Projects

Learn more about using a coding agent with your Stripe Projects account.

More collaborations with Databricks and Stripe

In addition to Stripe Projects, Databricks is also announcing the Stripe Data Pipeline, now available on the Databricks Marketplace. Learn more about how Stripe customers can analyze payment and business data directly in their Databricks account - no ETL required.