The Syncari Synapse for Databricks enables bidirectional synchronization, supporting both watermark and non-watermark entity sync between Databricks tables and Syncari entities.
How it Works
Using a unique identifier and optional timestamp column from Databricks tables, Syncari synchronizes data in near real-time into Syncari entities. Syncari supports both incremental (watermarked) and full (non-watermarked) sync modes.
Changes made in Databricks or in other connected systems are automatically processed by Syncari’s data fabric — including conflict resolution, deduplication, enrichment, and cleansing.
Unified, high-quality records can then be pushed back to Databricks for analytics, machine learning, and reporting.
Supported Objects and Workflow
Syncari can synchronize with any Databricks table that includes:
- A primary key
- (Optional) A last-updated timestamp field (for watermark sync)
Data can be pulled from or written to Delta Lake tables, enabling seamless collaboration between Syncari and your AI/analytics workflows. Both full and incremental syncs are supported, depending on your configuration.
Get started with Syncari for Databricks
Try Syncari today or request a custom demo to see how Syncari can simplify data unification and governance for your Lakehouse analytics stack.