Data lake upstart Upsolver takes aim at Databricks

The San Francisco-based startup has released a SQL-based, self-orchestrating data pipeline platform, claiming it will go to go toe-to-toe with Databricks’ Delta Live Tables.

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San Francisco-based startup Upsolver is launching a new service, dubbed SQLake, that company officials say will take on Databricks’ Delta Live Tables to meet enterprise demand for SQL-oriented, data pipeline automation.

SQLake, just like Delta Live Tables, is looking to lower the barriers to entry for complex data work, such as keeping ETL (extraction, transformation, transport, and load) pipelines healthy, by using SQL as the preferred language.

Generally available now, SQLake offers a SQL-based, self-orchestrating data pipeline that treats all data as data in motion, thereby automatically parsing the dependencies between each step in the pipeline to optimize the flow of data, the company said.

SQL is the most popular data query language and attracts users including data engineers, data scientists, analysts, product managers, and other data consumers within an enterprise.

Upsolver is offering pricing aimed to attract user attention to a new alternative for data pipeline automation. The new service is available for $99 per TB of data ingested with no minimum commitment, the company said, adding that the new service was available on AWS Marketplace with the option to run a 30-day free trial.

Upslover, founded in 2015 by data engineers Ori Rafael and Yoni Ein, counts Cox Automotive, IronSource, ProofPoint and Wix among its customers. The company is headquartered in San Francisco, with R&D centered in Tel Aviv.

Investors include Scale Venture Partners, Vertex Ventures US, Wing Venture Capital, and JVP.

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