New capabilities—including real-time UniForm table streaming and Iceberg optimisation—accelerate Delta/Iceberg interoperability, trusted data products, and AI-ready pipelines for Mosaic AI
San Francisco, CA– Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence, has announced a series of new capabilities for customers of Databricks, the Data and AI company, built on the Databricks Data Intelligence Platform. These enhancements include streaming real-time data into Unity Catalog’s Uniform tables via change data capture (CDC), automated Apache Iceberg™ optimisation through Qlik Open Lakehouse, and the creation of high-quality data products.
These enhancements give data teams greater flexibility across open formats, improve operational performance with Delta and Iceberg data, and accelerate the path to trusted, AI-ready architectures, without compromising Databricks-native governance or performance.
New capabilities include:
- Real-Time Data Streaming to Databricks Uniform Tables via CDC: Qlik Replicate® now streams continuous CDC from enterprise data sources directly into Unity Catalog’s managed Iceberg tables, enabling low-latency ingestion that supports strict business SLAs for both Delta and Iceberg formats.
- Adaptive Iceberg Optimisation: As data is ingested into Apache Iceberg tables by Qlik Talend Cloud®, Qlik Open Lakehouse’s fully automated optimiser will intelligently handle compactions, partitioning, and pruning, reducing storage footprint and delivering faster queries. Optimised Iceberg tables will be queryable via Databricks Photon or any Iceberg-compatible engine with consistently low-latency performance.
- High-Quality, AI-Ready Data Products: Enables data teams to build governed Data Products and push down data quality computation for Databricks assets—including Delta Live Tables—ensuring products remain trusted, accurate, and ready for AI use cases.
- Spark-Aware Studio Roadmap Enhancements: Qlik will soon introduce new developer-focused capabilities including schema inference, Databricks notebook import, and native Spark debugging—empowering teams to manage governed, self-service data pipelines within their existing Databricks workflows.
“Databricks customers continue to push the boundaries of what’s possible with open data formats and AI,” said Ariel Amster, Director, Strategic Technology Partners at Databricks. “By delivering real-time change data capture into UniForm tables and its native integration with Mosaic AI, Qlik is helping our joint customers simplify and accelerate innovation on the Databricks Data Intelligence Platform.”
“From ingestion to insight, Databricks customers are demanding more speed, flexibility, and trust across their data estate,” said David Zember, Senior Vice President of Worldwide Channels and Alliances at Qlik. “These new capabilities allow teams to do more with their Databricks investment—especially around governance, interoperability, and AI readiness.”
The new capabilities—including Uniform table CDC and Iceberg optimisation—are now available in private preview. Qlik’s planned Open Lakehouse integration for Databricks is under development with timing to be announced. To learn more, request early access or see a demo, visit our website.
