Singapore – Feb 25, 2020 – Qlik today announced it has expanded its partnership with Databricks, joining Databricks’ Data Ingestion Network. Qlik Data Integration simplifies loading data into Delta Lake, an open-source project that provides reliable data lakes at scale, accelerating the creation of lakehouses for analytics and machine learning (ML). Lakehouse, a new data management paradigm, combines elements of data lakes and data warehouses, enabling business intelligence (BI) and ML on all of a business’s data.
“We’re excited to be one of the inaugural partners for the launch of Databricks’ Data Ingestion Network. This is the latest development in our growing relationship focused on helping enterprises accelerate time to value with data in the cloud,” said Itamar Ankorion, SVP of Technology Alliances at Qlik. “Our deeper integration provides Databricks’ customers with a more seamless on-ramp of data from any enterprise data source to their Delta Lake, with the best-fit modern data integration strategy to fuel future targets as their data platforms evolve.”
Qlik and Databricks have been jointly delivering integrated solutions and tremendous value to customers looking to accelerate their journey to the cloud. Deploying Qlik Data Integration with Delta Lake allows unparalleled ability to automate and stream data from any source, including mainframes, SAP, databases and data warehouses, into the cloud, in real-time. Customers can quickly unlock the value of all their data for analysis and ML with analytics-ready data sets to maximize the efficiency, scalability and cost-savings in the cloud.
“Databricks is excited to have Qlik as a key partner in the launch of our Data Ingestion Network. The Qlik Data Integration platform will bring organizations a market-leading data integration solution to move all their data into a lakehouse,” said Michael Hoff, SVP of Business Development and Partners at Databricks. “Customers will see the benefit in easily bringing real-time and analytics-ready data directly into Delta Lake for their BI and ML use cases.”