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Delta Sharing

An open standard for secure sharing of data assets

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Databricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform.

Key benefits

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Open cross-platform sharing

Avoid vendor lock-in, and easily share existing data in Delta Lake and Apache Parquet formats to any data platform.

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Share live data with no replication

Share live data across data platforms, clouds or regions without replicating or copying it to another system.

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Centralized governance

Centrally manage, govern, audit and track usage of the shared data on one platform.

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Marketplace for data products

Build and package data products, including data sets, ML models and notebooks once and distribute anywhere through a central marketplace.

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Privacy-safe data cleanrooms

Easily collaborate with your customers and partners on any cloud via a secure hosted environment while safeguarding data privacy.

How it works

Native Integration

Native integration with the Databricks platform

Native integration with the Unity Catalog allows you to centrally manage and audit shared data across organizations. This lets you confidently share data assets with suppliers and partners for better coordination of your business while meeting security and compliance needs.

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Easily manage shares

Create and manage providers, recipients, and shares with a simple-to-use UI, SQL commands or REST APIs with full CLI and Terraform support

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Discover and access data products through an open marketplace

Easily discover, evaluate and gain access to data products including data sets, machine learning models, dashboards and notebooks from anywhere, without the need to be on the Databricks platform.

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Privacy-safe data cleanrooms

Collaborate with your customers and partners on any cloud in a privacy-safe environment. Securely share data from your data lakes without data replication. Meet collaborators on their preferred cloud and provide them the flexibility to run complex computations and workloads in any language — SQL, R, Scala, Java and Python. Guide collaborators through common use cases using predefined templates, notebooks and dashboards, accelerating time to insights.

Use cases

Build Data Mesh with Delta Sharing to securely share data with business units and subsidiaries across clouds or regions without copying or replicating the data.

Customers

Nasdaq

“Delta Sharing helped us streamline our data delivery process for large data sets. This enables our clients to bring their own compute environment to read fresh curated data with little-to-no integration work, and enables us to continue expanding our catalog of unique, high-quality data products.”

— William Dague, Head of Alternative Data
SafeGraph

“As a data company, giving our customers access to our data sets is critical. The Databricks Lakehouse Platform with Delta Sharing really streamlines that process, allowing us to securely reach a much broader user base regardless of cloud or platform.”

— Felix Cheung, VP of Engineering
Pumpjack

“Leveraging the powerful capabilities of Delta Sharing from Databricks enables Pumpjack Dataworks to have a faster onboarding experience, removing the need for exporting, importing and remodeling of data, which brings immediate value to our clients. Faster results yield greater commercial opportunity for our clients and their partners.”

— Corey Zwart, Head of Engineering
YipitData

“With Delta Sharing, our clients can access curated data sets nearly instantly and integrate them with analytics tools of their choice. The dialogue with our clients shifts from a low-value, technical back-and-forth on ingestion to a high-value analytical discussion where we drive successful client experiences. As our client relationships evolve, we can seamlessly deliver new data sets and refresh existing ones through Delta Sharing to keep clients appraised of key trends in their industries.”

— Anup Segu, Data Engineering Tech Lead

An open ecosystem

Access the latest published version directly from the provider in easy-to-use SQL, Python or BI tools.

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