--- title: "Delta Sharing" description: "6 posts about Delta Sharing, summarised, each linking to the original." --- # Delta Sharing > 6 posts about Delta Sharing, summarised, each linking to the original. ## Articles ### [Advancing Apache Iceberg on Databricks: Iceberg v3 GA, Open Sharing, and Unified Governance](https://yomu.fyi/post/advancing-apache-iceberg-on-databricks-iceberg-v3-ga-open-sharing-and.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Jason Reid, Ryan Blue, Daniel Weeks, Michelle Leon - Published: May 28, 2026 Databricks announces a broad set of Apache Iceberg capabilities in Unity Catalog, spanning General Availability, previews, and beta releases. Managed Iceberg is GA, supporting table creation, reads, writes, optimization, governance, and sharing, while Iceberg v3 adds deletion vectors, row tracking, and VARIANT across managed, foreign, and UniForm-enabled tables. Unity Catalog also federates external catalogs, vends credentials, shares live data with Iceberg REST-compatible clients through Delta Sharing, and applies attribute-based access control during server-side scan planning for supported external engines. These capabilities are presented as a unified approach to open APIs, cross-engine governance, zero-copy sharing, and production performance without copying data. The post also outlines Iceberg v4 and a proposal for Delta 5.0 to adopt an adaptive metadata tree structure. ### [Unlocking SAP business context in Databricks with semantic metadata Delta Sharing](https://yomu.fyi/post/unlocking-sap-business-context-in-databricks-with-semantic-metadata-de.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Akram Chetibi, Katie Cummiskey, Moe Derakhshani, Abhijit Chakankar - Published: Apr 30, 2026 SAP Business Data Cloud now offers generally available semantic metadata synchronization with Databricks Unity Catalog for mounted SAP BDC Delta Shares. When a table is accessed, Unity Catalog receives table-level business-friendly display names, descriptions, context, and governance tags, while SAP BDC remains the single source of truth and subsequent changes are reflected. The capability builds on BDC Connect and Delta Sharing, allowing governed SAP data products to be discovered and combined with other enterprise sources without recreating business context or governance separately. Column descriptions, table relationships such as primary and foreign keys, and PersonalData namespace tags give Databricks AI Assistant and AI/BI Genie explicit context for natural-language questions and join-ready queries. The stated result is more understandable, discoverable, and AI-ready SAP data, with automated classification signals supporting compliance, access control, and responsible AI. ### [Stripe data now available on Databricks via Databricks Marketplace](https://yomu.fyi/post/stripe-data-now-available-on-databricks-via-databricks-marketplace.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Justin Fenton, Harish Gaur, Matt Napoli - Published: Apr 29, 2026 Stripe Data Pipeline is now available on Databricks Marketplace through Delta Sharing, allowing payment and business data to be analyzed in a Databricks workspace without ETL. Stripe data—including transaction records, customer histories, subscriptions, refunds, and payouts—remains in Stripe’s infrastructure and is queried directly through Unity Catalog, where it can be joined with other tables. The approach replaces polling integrations and custom jobs, avoiding per-call charges, connector licensing fees, data duplication, and maintenance code while providing row- and column-level access controls, audit trails, and compliance features. The shared data is positioned for AI-native uses such as continuous transaction monitoring, churn scoring, LLM-powered retention workflows, Genie queries, and finance analytics apps. Getting started involves visiting the Stripe Data Pipeline listing on Databricks Marketplace. ### [Powering KPMG UK Audit's AI future with Databricks](https://yomu.fyi/post/powering-kpmg-uk-audit-s-ai-future-with-databricks.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Mark Wallington, Greta Nasai - Published: Apr 27, 2026 KPMG UK is evolving its Audit data platform with Databricks to support AI-enabled analytics while preserving governance, rigour, and professional standards. The program converges structured data, advanced analytics, and AI on a unified cloud-native Lakehouse, with Databricks SQL replacing core SQL Server workloads and Delta underpinning the platform. Lakebridge assessed migration complexity, while Databricks-hosted large language models including Claude Sonnet and Genie Code helped convert T-SQL, refactor stored procedures, modularize queries, and suggest Delta-based optimizations under engineer review. This reduced refactoring time by around 60% and enabled modernization of more than 400 scripts and stored procedures in roughly three months. Databricks SQL Serverless provides elastic compute for spiky workloads, while Genie offers traceable, version-controlled SQL and Delta Sharing supports governed data exchange. ### [Bridging data science and marketing: Databricks unveils Delta Sharing integration for Adobe Experience Platform and agentic marketing workflows](https://yomu.fyi/post/bridging-data-science-and-marketing-databricks-unveils-delta-sharing-i.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Justin Fenton, Dan Zuckerberg, Katy Yuan - Published: Apr 20, 2026 Databricks and Adobe announce three partnership milestones aimed at connecting governed Lakehouse data with marketing activation in Adobe Experience Platform. The changes include Delta Sharing support for zero-copy access, a Databricks Genie connection to Adobe Marketing Agent through Model Context Protocol (MCP), and an upcoming Adobe Marketing Agent beta for the Databricks Marketplace. Using Unity Catalog as the source, Experience Platform can access shared tables and views as virtual tables, while Adobe Data Distiller queries live Databricks data without copying underlying records. Through MCP, agents in both platforms can use governed datasets, metadata, models, campaign metrics, SQL Warehouses, and Model Serving endpoints with natural-language interactions. The stated outcome is a shared, real-time context for audience creation, campaign analysis, closed-loop attribution, and model improvement, while reducing data movement, duplication, latency, egress, and governance overhead. ### [Mercedes-Benz builds a cross-cloud data mesh with Delta Sharing and intelligent replication, cutting costs by 66%](https://yomu.fyi/post/mercedes-benz-builds-a-cross-cloud-data-mesh-with-delta-sharing-and-in.md) - Company: [Databricks](https://yomu.fyi/company/databricks.md) - Author: Alexander Summa, Aleksandar Dragojevic - Published: Apr 20, 2026 Mercedes-Benz built a cross-cloud data mesh to share after-sales data between AWS and Azure while supporting its data-defined vehicle strategy. Existing direct queries incurred egress costs, and weekly full loads delayed updates for datasets that included vehicle over-the-air events and workshop visits; source tables were in Iceberg while many consumers expected Delta. Using Unity Catalog and Delta Sharing, the company federated AWS Glue tables, established cross-metastore shares, and used periodic serverless Sync Jobs with Delta Deep Clone to incrementally replicate selected tables into Azure object storage for local querying. This hybrid model preserves direct sharing for fresher workloads while reducing transfer for less time-sensitive ones. For the initial ten data products, egress costs fell 66%, update frequency improved from weekly to every second day, and the source reports an approximately 93% annual reduction in its 50-use-case comparison.