Databricks Marketplace — How to Use & Share Data Products
Imagine a digital bazaar where every dataset, feature table, and machine learning model you need is just a click away.
Welcome to Databricks Marketplace — the central hub for discovering, sharing, and monetizing high-quality data products across organizations and industries.
In this article, you’ll learn what Databricks Marketplace is, how to use it, and best practices for sharing data products in a secure, governed way.
🏛️ What Is Databricks Marketplace?
Databricks Marketplace is a one-stop marketplace for data and analytics assets within the Databricks Lakehouse ecosystem.
Think of it as:
- A data app store: You can browse datasets, feature tables, ML models, and notebooks
- A secure sharing platform: Share internally with your teams or externally with partners
- A monetization channel: Sell premium data products or analytics content
Marketplace integrates with Unity Catalog, ensuring secure access controls, lineage tracking, and governance.
🔍 Key Features of Databricks Marketplace
-
Discover Ready-to-Use Data Products
- Public datasets (financial, healthcare, geospatial)
- Feature tables for ML pipelines
- Notebooks and dashboards
-
Secure Data Sharing
- Governed sharing with fine-grained access
- Works across clouds (AWS, Azure, GCP)
- Integrated with Unity Catalog for access control
-
Monetize Your Data
- Publish data products for external partners
- Track usage, subscriptions, and licensing
- Create recurring revenue from high-value data
-
Seamless Integration
- Directly query Marketplace datasets using SQL or PySpark
- Integrate into existing ETL pipelines and ML workflows
🚀 How to Use Databricks Marketplace
1. Discovering Data Products
- Navigate to the Marketplace tab in your Databricks workspace
- Browse by category: Datasets, ML models, notebooks, features
- Use filters: industry, format, provider, freshness
Tip: Always check data quality, lineage, and usage restrictions before integrating into pipelines.
2. Sharing Data Products Internally
- Create a data product in your workspace
- Register it with Unity Catalog
- Assign permissions for specific teams, users, or groups
- Users can now access the data seamlessly through SQL, Python, or notebooks
3. Publishing for External Partners
- Use the Databricks Partner Marketplace
- Define licensing and access controls
- Share the product securely while maintaining governance
- Track subscriptions and usage metrics
Example: A retail company can share aggregated sales insights with suppliers without exposing raw transactional data.
4. Best Practices for Marketplace Usage
- Leverage Unity Catalog for governance — ensures security and auditability
- Document metadata clearly — helps users understand and trust your data
- Version your datasets — prevents breaking downstream pipelines
- Monitor usage and performance — identify which products deliver value
🧩 Story: How a Team Benefits from Databricks Marketplace
Meet Lina, a data engineer at a fintech startup.
Her team struggles with inconsistent data sources for fraud detection.
Before Marketplace:
- Multiple duplicate datasets
- Hard-to-track updates
- Slow model training
After Marketplace:
- Published curated feature tables for fraud detection
- Analysts and ML engineers discover products quickly
- Teams reduce model development time by 30%
Databricks Marketplace allowed Lina’s team to collaborate efficiently, share insights securely, and scale analytics faster.
🏁 Summary
Databricks Marketplace is more than a catalog — it’s a collaboration, governance, and monetization hub for data and analytics products.
- Discover high-quality datasets
- Share securely within or outside your organization
- Monetize data for external partners
- Integrate seamlessly with Lakehouse workflows
By leveraging Marketplace, teams can accelerate analytics, ML, and data-driven innovation.
📌 Continue to Next Topic
👉 Databricks System Tables Overview — Usage, Billing & Audit Data