Source: Businesswire India
Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence, today announced the launch of Qlik Open Lakehouse, a fully managed Apache Iceberg solution built into Qlik Talend Cloud. Designed for enterprises under pressure to scale faster and spend less, Qlik Open Lakehouse delivers real-time ingestion, automated optimization, and multi-engine interoperability — without vendor lock-in or operational overhead.
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This marks a major step forward in the evolution of modern data architectures. As organizations accelerate AI adoption, the cost and rigidity of traditional data warehouses have become unsustainable. Qlik Open Lakehouse offers a new path: a fully managed lakehouse architecture powered by Apache Iceberg that delivers 2.5x–5x faster query performance and up to 50% lower infrastructure costs, while maintaining full compatibility with the most widely used analytics and machine learning engines.
“Performance and cost should no longer be a tradeoff in modern data architectures,” said Mike Capone, CEO of Qlik. “With Qlik Open Lakehouse, enterprises gain real-time scale, full control over their data, and the freedom to choose the tools that work best for them. We built this to meet the demands of AI and analytics at enterprise scale — without compromise.”
Qlik Open Lakehouse is built from the ground up to meet the scale, flexibility, and performance demands of modern enterprises — without the tradeoffs. It combines real-time ingestion, intelligent optimization, and true ecosystem interoperability in a single, fully managed platform.
"Enterprises are increasingly adopting lakehouse architectures to unify data across on-premises and cloud environments," said Matt Aslett, Director of Research, Analytics and Data at ISG Software Research. "Qlik Open Lakehouse, which leverages open standards such as Apache Iceberg, is well-positioned to meet the growing demand for real-time data access and multi-engine interoperability, enabling enterprises to harness the full potential of their data for AI and analytics initiatives."
As AI workloads demand faster access to broader, fresher datasets, open formats like Apache Iceberg are becoming the new foundation. Qlik Open Lakehouse responds to this shift by making it effortless to build and manage Iceberg-based architectures — without the need for custom code or pipeline babysitting. It also runs within the customer’s own AWS environment, ensuring data privacy, cost control, and full operational visibility.
“Qlik Open Lakehouse initiative is a significant development we're keenly watching,” shared David Navarro, Data Domain Architect at Toyota Motor Europe. “Large corporations like ours urgently need interoperability between diverse business units and partners, each managing its own technology stack and data sovereignty. Apache Iceberg is emerging as the key to zero-copy data sharing across vendor-independent lakehouses, and Qlik's commitment to delivering performance and control in these complex, dynamic landscapes is precisely what the industry requires.”
Qlik Open Lakehouse is available now in private preview and is scheduled to be generally available in July 2025. Private preview is limited — early access is encouraged for teams looking to modernize ahead of GA. To learn more and request early access, visit our website or connect with us at Qlik Connect, May 14–17 in Orlando.
About Qlik
Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML, data integration, and analytics. Our AI/ML tools, both practical and scalable, lead to better decisions, faster. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive.
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