Databricks also makes BI and SQL available serverless

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With its Lakehouse architecture for data analysis in the cloud, Databricks wants to bridge the gap between traditional business intelligence (BI) and modern machine learning applications. The SQL Analytics service, which is based on Delta Lake, offers its own interface for queries and the visualization of results, including a connection to popular business intelligence tools such as Tableau, Qlik or Power BI. Now the provider is announcing a new, fully managed service that delivers BI and SQL computations to analysts on demand: Databricks Serverless SQL.

The cloud service is based on a computing platform configured and operated by Databricks, which comprises three separate levels, from the runtime on Kubernetes to the container in a virtual machine and the workspace in a virtual network. It should be possible to easily connect common BI tools via integrated connectors with optimized JDBC / ODBC drivers that also support authentication. Compared to third-party cloud data warehouses, Databricks for Serverless SQL promises shorter startup times and faster query execution. Due to the “pay per use” approach and the low management effort, users should also benefit from lower costs.

Databricks Serverless SQL is now available as a public preview on AWS. Further information on the new service can be found in the blog post on the announcement.

The speculation about an IPO of Databricks, which has been circulating for a long time, is likely to receive new nourishment in view of a further round of financing. One led by Counterpoint Global (Morgan Stanley) Series H funding brings $ 1.6 billion of fresh capital to Databricks. It was only at the beginning of the year that the company behind the big data framework Apache Spark was able to raise around one billion US dollars. The total amount of funding currently reaches nearly 3.5 billion US dollars, the valuation of the company rises to 38 billion US dollars. The IPO expected for the current year should thus come a step closer.


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