Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence, announced at Snowflake’s annual user conference, Snowflake Summit 2025, the launch of native support for Snowflake-managed Apache Iceberg™ tables, enabling fast, open-format data pipelines directly into Snowflake’s highly performant, governed environment. Alongside this, Qlik is introducing additional capabilities that allow customers to leverage Qlik Open Lakehouse, powered by Apache Iceberg, in conjunction with Snowflake for greater architectural flexibility and AI scalability.

These advancements are designed to help Snowflake customers reduce latency, optimise storage and compute efficiency, and accelerate the development of AI-powered applications, including retrieval-augmented generation (RAG) via Snowflake Cortex AI.

Newly announced capabilities include:

·      Native Streaming to Snowflake-managed Iceberg Tables: Qlik Talend Cloud® now supports continuous change data capture (CDC) from enterprise systems directly into Snowflake-managed Iceberg tables, enabling low-latency ingestion supporting strict business SLAs for analytics and AI use cases.

·      Qlik Open Lakehouse Optimisation & Mirroring: Qlik Open Lakehouse combines low-latency ingestion into Apache Iceberg tables with an automated optimiser that manages compactions, partitioning, and pruning in S3—delivering faster queries and a reduced storage footprint without manual tuning. It also mirrors Iceberg data back into Snowflake for downstream transformations without duplicating data.

·      One-Click Data Products with In-Snowflake Quality Execution: Qlik data products can be generated directly within customers’ Snowflake ecosystems, leveraging the Qlik Talend Trust Score™ to push down data quality computation in Snowflake—enabling teams to produce governed, high-quality outputs that elevate the value of curated assets.

·      Knowledge Mart for RAG on Snowflake Cortex: Qlik’s Knowledge Mart transforms structured and unstructured content—including PDFs, call transcripts, and relational records—into AI-ready vectorised assets in Snowflake, powering retrieval-augmented generation pipelines through Cortex with full explainability and governance. 

“Open standards like Apache Iceberg are foundational to an interoperable data stack, including both Qlik and Snowflake,” said Saurin Shah, Senior Product Manager, Data Engineering at Snowflake. “By combining real-time ingestion, automated optimisation, and Cortex-ready AI pipelines, Qlik, together with Snowflake, helps customers accelerate time to insight while maximising the value of their data investments.” 

“The integration between Qlik and Snowflake has transformed how we manage and operationalise data,” said Michael Benassi, Vice President of Enterprise Analytics at United Federal Credit Union. “By operationalising near real-time data ingestion and streamlined engineering pipelines, we’re able to scale insights across the business and support faster, more trusted AI initiatives.”

“This launch gives our joint customers the power to do more with their Snowflake investment,” said David Zember, Senior Vice President of Worldwide Channels and Alliances at Qlik. “By combining Qlik’s real-time ingestion and Iceberg optimisation with native Snowflake governance, we’re unlocking a smarter path to analytics and AI that’s as open as it is scalable.”

The new Qlik capabilities are now available in private preview, with general availability targeted in July 2025.