Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), has announced the general availability of Qlik Open Lakehouse, a fully managed Apache Iceberg service in Qlik Talend Cloud® that delivers real-time pipelines, automated Iceberg optimisation, and true multi-engine access without lock-in. The result is an AI-ready data foundation that cuts time and cost between data and action.

Deployed in the customer’s own cloud account with bring-your-own-compute, Qlik Open Lakehouse combines change data capture (CDC) ingestion with automatic Iceberg optimisation and multi-engine access so teams can use the tools they already rely on, including Amazon Athena, Snowflake, Spark, Trino, and Amazon SageMaker for machine learning (ML). In preview, customers reported faster queries and meaningfully lower infrastructure costs as they shifted workloads from proprietary warehouses to open, optimised Iceberg tables.

“AI stalls when data is slow, fragmented, and expensive,” said Mike Capone, CEO of Qlik. “Qlik Open Lakehouse fixes that by giving teams a real-time, Iceberg-based foundation they can run in their cloud at enterprise scale and query with the engines they already use. It brings performance, cost control, and governance into one motion so decisions happen faster and models improve every day.”

What’s new

• General availability of Qlik Open Lakehouse in Qlik Talend Cloud, deployed in the customer’s VPC with bring-your-own-compute for full security, performance, and cost control
• Multi-engine access on day one, including Amazon Athena support so teams can query Iceberg tables serverlessly alongside Qlik analytics and other engines
• SageMaker-ready data stored in governed Iceberg tables on Amazon Simple Storage Service (Amazon S3), making it easier for ML teams to access, prepare, and train models without building additional data copies
• Automatic Iceberg optimisation for compaction, partitioning, and metadata maintenance to improve query performance and reduce storage footprint
• Low-latency pipelines from hundreds of sources using CDC, with built-in data quality, lineage, cataloguing, and FinOps observability
• Qlik Analytics™ and AI on top with the Qlik engine and workflow automation so insights can trigger actions in business systems

“The general availability of Qlik Open Lakehouse translates Qlik’s long-term strategy into a tangible reality for companies adopting open table formats,” said Mike Leone, Principal Analyst, Enterprise Strategy Group. “Its ability to handle large amounts of data quickly, optimise it in real time, and work with different tools in the cloud solves common problems with data being out of date, slow, or expensive. Because it also has Qlik’s robust integration and data governance, it provides a strong platform for AI and analytics that teams can adopt without having to completely rebuild their systems or switch to new tools.”

Why it matters

AI value is bottlenecked by data. Qlik Open Lakehouse closes that gap by giving enterprises data and analytics foundations for AI: trusted, explainable, and up-to-date data in an open format that any engine can query. The result is faster decision-making, lower total cost, and freedom of choice across analytics and ML. In preview, customers saw up to 5x faster query performance and up to 50 percent lower infrastructure cost as they removed unnecessary copies and tuned Iceberg tables at scale.

How it works

• Open by design: Data lives in Apache Iceberg on customer object storage. The same tables are queryable from Qlik, Amazon Athena, Snowflake, Spark, Trino, and ML services like Amazon SageMaker.
• Real time by default: CDC keeps tables current. Automatic optimisation maintains performance as data grows.
• Governed and trusted: Integrated data quality rules, lineage, cataloguing, and access controls provide the assurance AI and regulated workloads require.
• Built for action: The Qlik engine and automation connect insight to workflow, so teams do not stop at dashboards.

Availability

Qlik Open Lakehouse is available today for Qlik Talend Cloud customers, including Amazon Athena support. SageMaker integration for model training and inference on Iceberg data is supported via standard AWS patterns. Additional ecosystem updates are targeted for Q4 2025.