Qlik Adds Native Support for Snowflake Managed Iceberg Tables
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, optimize 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 Optimization & Mirroring: Qlik Open Lakehouse combines
low-latency ingestion into Apache Iceberg tables with an automated optimizer
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 vectorized 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 optimization, and Cortex-ready AI pipelines, Qlik,
together with Snowflake, helps customers accelerate time to insight while
maximizing the value of their data investments.”
“The integration between Qlik and Snowflake has transformed
how we manage and operationalize data,” said Michael Benassi, Vice President of
Enterprise Analytics at United Federal Credit Union. “By operationalizing 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 optimization 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. To request early
access, see a live demo, or speak with Qlik product experts, visit booth #1219
at Snowflake Summit 2025 or visit us online.
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