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Databricks

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 Databricks and Stripe Projects: Infrastructure Built for Agents 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? Introducing Genie Agent Mode Governing coding agent sprawl with Unity AI Gateway Governing Coding Agent Sprawl with Unity AI Gateway What is pgvector? Banks Don’t Have an AI Problem – They Have a Data Platform Problem Open Platform, Unified Pipelines: Why dbt on Databricks is Accelerating Why Your Agents Can’t Read Enterprise Documents — and How to Fix It Building with Databricks Document Intelligence and Lakeflow Databricks on Google Cloud: Innovate Faster. Smarter. Together. Introducing the Databricks Connector for Google Sheets: Real-Time, Governed Lakehouse Data in the Sheets Users Love Unity AI Gateway: How to connect agents to external MCPs securely Expanding agent governance with Unity AI Gateway Agentic reasoning in practice: Making sense of structured and unstructured data Agent Bricks: The Governed Enterprise Agent Platform 8 AI and data trends shaping financial services in 2026 Building real-time product search on Databricks Lovable + Databricks: Build Data-Driven Apps at the Speed of Thought Memory scaling for AI agents Powering clinical research innovation: How TriNetX uses Databricks to accelerate drug development Database Branching in Postgres: Git-Style Workflows with Databricks Lakebase How Zalando built a unified data foundation for AI and analytics on Databricks The next era of the open lakehouse: Apache Iceberg™ v3 in Public Preview on Databricks How FSIs eliminate silos between clients, operations, and finance How MakeMyTrip achieved millisecond personalization at scale with Databricks A multi-agent approach to audience intelligence AiChemy: Next-generation agent with MCP, skills and custom data for drug discovery Accelerate business insights with Lakeflow Connect, now with a Free Tier Unlocking Next-Gen Customer Experiences with Data Intelligence for Marketing
Announcing Apps on Databricks Marketplace
Tia Chang · 2026-06-17 · via Databricks

Data intelligence is reshaping how organizations turn data into outcomes. Teams no longer just want raw datasets - they want applications that put data to work immediately, like interactive dashboards, custom AI agents, and specialized analytics tools. Some of these apps run entirely on a customer's own data, and others pair a provider's proprietary data or logic with the customer's. 

Last year, we launched Databricks Apps, enabling teams to natively build and deploy secure data and AI applications using popular frameworks like Streamlit, Dash, and Gradio for Python and React, Angular, Svelte, and Express for Node.js. Today, we are taking the next major step in democratizing data and AI applications.

We are thrilled to announce the Public Preview of Apps on Databricks Marketplace. Databricks customers can now discover, install, and run third-party data and AI applications directly inside their secure Databricks workspaces. For software vendors and data providers, this opens up a seamless, no-egress distribution channel to deliver immediate, interactive value to thousands of enterprises worldwide.

Launch Partners for Apps on Markletplace

The Challenge: The "Last Mile" of Third-Party App Procurement

Historically, adopting a new third-party analytics tool or data application has been a security and engineering nightmare. For enterprise data teams, the process typically involves:

  • Moving sensitive corporate data out of a secure environment to an external vendor’s infrastructure.
  • Weeks or months of Infosec and compliance reviews to ensure the external app meets strict security standards.
  • Complex setup involving custom ETL pipelines, API integrations, and fragmented identity management.

Apps on Databricks Marketplace completely flips this model. Instead of moving your data to the application, the application comes to your data.

Key Capabilities of Apps on Databricks Marketplace

Databricks Marketplace is an open marketplace for data as well as AI and analytics assets such as ML models, notebooks, applications.. By embedding application sharing directly into the Databricks Marketplace ecosystem, we are introducing a fast, unified, and enterprise-ready way to consume third-party software.

1. Seamless Discovery and One-Click Installation

Users can browse a rich catalog of apps built by top-tier industry partners. Once you find an app that fits your needs, installation takes just a few clicks, automatically provisioning the application natively inside your workspace.

2. Built-in Governance with Unity Catalog

Every third-party app installed from the Marketplace runs in a secure, isolated sandbox inside the consumer's Databricks account, where it inherits the security, auditing, and fine-grained access controls of Unity Catalog. Each app declares exactly which resources and scopes it needs, and the consumer explicitly authorizes them at install time. 

3. A Massive New Distribution Channel for ISVs and SaaS Providers                                                                                                                       

For providers, having to separately integrate, set up infrastructure, review compliance, and support every time a new customer is onboarded is a huge headache. With Apps on the Marketplace, providers publish once, and any Databricks customer can discover, request access, install, and run an app entirely within their own environment, with no vendor infrastructure to maintain and no per-customer onboarding overhead. Because the app runs natively on the customer's Databricks compute, procurement and compliance hurdles drop sharply, drastically shortening the B2B sales cycle.

4. Security and IP Protection, By Design

Apps on Databricks Marketplace inherit the security and governance posture of the Databricks Platform, and add provider-side protections that traditional procurement models can't offer.

  • Closed-source by default. Provider apps ship as closed-source containers. The consumer installs and runs the app in their workspace, but never sees the underlying code. Provider IP is protected end-to-end.
  • Consumer-controlled egress. Apps execute inside the consumer's Databricks account on serverless compute, with the same isolation as the rest of Databricks Apps — dedicated compute per app, network segmentation, encryption at rest and in transit. Any external API calls or data movement an app needs are declared up front, authorized by the consumer admin at install, and governed by the workspace's Serverless Egress Gateway (SEG) policy. 
  • Compliance ready. Supported in all regions where the Databricks compliance security profile is available.

A Native Part of the Databricks Stack

Apps on Databricks Marketplace is a native part of the Databricks Platform, connecting directly to the rest of the stack:              

  • Unity Catalog for governance and data access.
  • SQL Warehouse for analytical queries against governed data.
  • Lakebase as a managed Postgres backend for app state, session storage, or low-latency operational data.
  • Model Serving and Foundation Model APIs for inference - apps that need AI capabilities can call serving endpoints natively, with no external LLM provider required.
  • Genie spaces and Agent Bricks for natural-language and agentic workflows embedded in the app experience.
  • And more…

This means many of the launching apps are AI-ready out of the box. Providers benefit too: building on these primitives is faster than wiring up external services, and the consumer's security review is simpler because there's nothing extra to allowlist.

Launching with an Elite Partner Ecosystem

We are proud to launch Apps on Databricks Marketplace alongside 20 partners building production-grade applications across data and AI. These applications span a range of industry use cases:

Apps on Marketplace Ecosystem

"Organizations want to collaborate on sensitive data, for measurement, enrichment, or AI,  but the mechanics of doing it securely have been painfully complex. To address this, we're excited to make Databolt Connect available as one of the first native applications on Databricks Marketplace. With Databolt Connect, users can securely prepare and link datasets within Databricks Clean Rooms without raw data ever leaving their environment, offering secure, friction-free collaboration at scale. And the Databricks Marketplace lets us put this in customers' hands instantly." — Vince Goveas, Director, Product Management, Capital One Software
“Advertisers, retailers, and commerce media partners are increasingly looking for simpler ways to activate data and insights to drive business outcomes. By making The Trade Desk Connector App available through Databricks Marketplace, we're helping brands, retailers, and media partners more seamlessly connect audience, targeting, conversion, and measurement data to advertising workflows. The integration streamlines activation by enabling teams to securely leverage data directly from their Databricks environment, making it easier to put data to work and drive more value from their investments across the open internet.” —Gabe Richman, GM of Data Partnerships at The Trade Desk
“Deploying Datavant’s tokenization technology as a native Databricks App eliminates the need for data movement. By building directly on Databricks, we allow clients to securely tokenize healthcare records right where their data already lives in a simple and intuitive manner. Combining our trusted tokenization with Unity Catalog’s governance means organizations can safely unlock clinical value in minutes instead of months.” —Sara Livengood, SVP Product Management, Datavant Life Sciences 
“Organizations are eager to scale Genie and AI across their lakehouse, but AI-ready data starts with AI-ready metadata - and for many teams, the effort required to curate context-rich, high-quality metadata is simply too large. That’s why we’re excited to bring StewardOps, our AI-Accelerated Metadata Generation app, to the Databricks Marketplace. It extracts business knowledge from your custom context sources, then turns them into Unity Catalog descriptions reviewed by data stewards before publishing.” — Noel Anson, Director, Databricks Business Unit, Slalom
“Data teams spend enormous effort translating complex business concepts - hierarchies, graph relationships, cross-database logic - into custom pipelines that break every time something changes.We're excited to launch the Prometheux app on Databricks Marketplace because it lets customers deploy our ontology engine and semantic layer directly into their workspace and start defining those concepts once, across all their connected sources. Prometheux compiles the logic into optimized pipelines automatically. Databricks Marketplace makes that accessible to every Databricks customer from day one.” — Davide Benedetto, CTO, Prometheux
“At Reflex, we believe the future of enterprise software is custom apps, not rigid off-the-shelf SaaS. With Reflex on the Databricks Marketplace, teams can build interactive applications in pure Python, connected natively to Unity Catalog and Lakebase and running entirely on Databricks' serverless runtime, with no app hosting to provision and no Javascript to maintain. It's the fastest path from Python straight to a production app." — Nikhil Rao, Co-Founder and CEO of Reflex

How It Works: From Discovery to Action

Getting started with Apps on Databricks Marketplace is simple and fits naturally into your existing workflow:

  1. Browse: Navigate to the Marketplace tab in your Databricks workspace and filter by the new Apps category.
  2. Install: Workspace admins select an application, review and authorize the permissions and resource bindings it needs, and click Install.    
  3. Launch: The app deploys onto a secure, serverless runtime in your workspace, generating a clean, dedicated URL.
  4. Use: Business and technical users open and use the app.

What's next

This is just the start, and we're excited to continue investing across the experience in the coming months:

  • Bundled assets: Listings that ship the app with its supporting jobs, notebooks, dashboards, and libraries together, so consumers don't need any manual setup pre-install.
  • Richer provider analytics: Per-listing usage, install funnels, and DBU consumption visibility for providers.
  • Commercial monetization for apps: Building on our in-platform monetization pilot to bring transactability to Marketplace apps.

Apps on Databricks Marketplace bridge the gap between secure data governance and powerful business software. By combining Marketplace's discovery layer with the native, in-workspace runtime of Databricks Apps, organizations can now safely adopt third-party software faster than ever before.

  • For Consumers: Explore the Databricks Marketplace today to discover and install third-party apps.
  • For Providers: Read our developer documentation to learn how to create, publish, and monetize your own applications on the Databricks Marketplace.