Databricks has announced the launch of Databricks Delta Engine, a high performance query engine on cloud data lakes. The company also revealed its acquisition of Redash, an open-source dashboarding and visualization service for data scientists and analysts. Databricks Delta Engine is purpose-built for use with Delta Lake, the company’s open-source structured transaction layer. The new query engine lets customers build curated data lakes that include structured and semi-structured data to run analytics.
Databricks offers a unified analytics platform that allows users to prepare and clean data at scale and continuously train and deploy machine learning models for AI applications. The product handles all analytic deployments, ranging from ETL to models training and deployment. It is also available as a fully managed service on Microsoft Azure and Amazon Web Services.
Databricks’ acquisition of Redash will enable the vendor to provide dashboarding and visualization capabilities on curated data lakes. According to Databricks: “Together, these enhancements enable organizations to adopt a single, simplified cloud architecture for data management, helping them significantly reduce costs and complexity and accelerate data team productivity.”
The new Delta Engine for Delta Lake enables query execution for data analytics and data science without moving the data out of the data lake. The open-source Redash project was created to help data teams make sense of their data by allowing users to gather an array of data sources into thematic dashboards. The results can be visualized in a number of formats including charts, cohorts, and funnels, and are easily shareable across an organization or with external users.
These announcements were made at the ongoing virtual Spark + AI Summit. To learn more, read Introducing Delta Engine in the Databricks blog, or check out the conference keynote on YouTube.
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