Qlikspecialist in integration, quality, analysis of data and Ia, has announced the availability of Qlik Open Lakehouseand Iceberg Apache Service totally managed in Qlik Talend Cloudwith which have real -time pipeinsautomatic iceberg optimization and access to any consultation engine. The result it offers is a database ready for AI with less time and cost between data and action.
Open Lakehouse can be implemented in the client’s cloud account with the “Bring Your Own Compute” modality, and combines intake through DCD (Change data captures) with automatic iceberg optimization and multimotor access, so that the equipment can use the tools they prefer. Among them, Amazon Athena, Snowflake, Spark, Trino and Amazon Sagemaker for automatic learning.
The value of the AI is conditioned by the data, and Qlik Open Lakehouse addresses the problem through the offer to database and analytical companies for AI, with reliable data, explainable and updated in an open format that can consult any engine. In this way, decision -making is expedited, and companies have freedom of choice in analytics and automatic learning.
During the Qlik Open Lakehouse test phase, customers who have tried the service have confirmed that they have managed to make consultations more quickly, in addition to lowering infrastructure costs. The latter is due to the fact that they have been able to transfer storage work loads to owner to open and optimized iceberg tables. The multimotor access allows you to consult these tables without server together with Qlik Analytics and other engines.
The service also has the data prepared for SageMaker, stored in Iceberg tables governed on Amazon S3, which facilitates automatic learning equipment access, preparation and training of models, without having to create additional copies of data. The data residing in Apache Iceberg on the storage of customer objects.
Automatic iceberg optimization for compaction, partitioning and metadata maintenance improves the performance of the consultations and reduces the storage space. As for the low latency pipelines that it uses with hundreds of sources via CDC, which maintains the updated tables, they have integrated data, lineage, cataloging and visibility of Finops. Open Lakehouse has qlik Analytics and the integrated with the Qlik engine and the automation of workflows, so that knowledge generates actions in business systems.
Qlik Open Lakehouse is already available for Qlik Talend Cloud customers, including compatibility with Amazon Athena. Integration with SageMaker for training and inference of data on Iceberg is compatible by standard AWS patterns. It is expected that in the last quarter of 2025 there are additional system updates.
Mike Capone, CEO de Qlikstressed that «the It stops when the data is slow, fragmented and expensive. Qlik Open Lakehouse solves this problem by providing the equipment with a real -time iceberg base that can be executed in their business scale and consult with the engines they already use. It provides performance, cost control and government in a single flow, so that decisions are made faster and models improve every day ».
