// AI news · 2026-11-07 · Databricks Blog
Implementing Incremental Data Sharing with OpenSharing
Databricks introduces OpenSharing to replace scheduled file or API feeds with live, incremental Delta table sharing.
Published 2026-11-07 06:13 (Beijing time)Source Databricks BlogAuto-summarised, fact-checked against source
01Summary
Recipients read directly from a shared table via Structured Streaming, automatically tracking new changes since the last checkpoint. The table maintains full change history and supports row-level inserts, updates, and deletes through Change Data Feed.
Summarised from the original article by an open-source model, then checked automatically: every number and English name must appear in the source. The original article is authoritative.
02Key points
- Recipients stream directly from shared Delta tables to track incremental changes automatically.
- Change Data Feed enables row-level inserts, updates, and deletes with full history retention.
- Providers share a single governed table without per-recipient export jobs or endpoints.
- Structured Streaming checkpoints ensure only new data is processed in each run.
03Source
Read, don't copy: replacing file feeds with OpenSharing - Part 2 (How to Implement)
Databricks Blog · published 2026-11-07 06:13 Beijing time
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