HPE acquires Ampool to bolster its Ezmeral software business

HPE said Ampool will help accelerate Ezmeral's analytics runtime for interactive SQL workloads and bolster its ability to handle data-intensive workloads.

HPE on Wednesday said that it's acquiring Ampool, makers of a data platform designed to boost Structured Query Language (SQL) processing speeds at scale. The financial terms of the deal were not disclosed. 

HPE said Ampool would join its Ezmeral software business to help accelerate Ezmeral's analytics runtime for interactive SQL workloads and to bolster its ability to handle data-intensive workloads.  

Launched last year, HPE Ezmeral runs and controls applications and data and also powers HPE GreenLake cloud services such as machine learning operations and containerization. HPE exited the software game in 2017 following the $8.8 billion spin-merge of its software portfolio with Micro Focus, but the launch of Ezmeral marked the return of the company's software efforts.

As for Ampool, HPE said the acquisition would bring in key technology components and open-source expertise that will expand the Ezmeral portfolio and reinforce HPE's investment, focus, and execution toward an open-source-based, IP-rich capability for the Ezmeral software line.

Over time, HPE said Ampool's technology would be turned into a set of SQL acceleration services made available through the HPE GreenLake cloud platform. 

"Our next focus area is to support SQL runtimes, specifically open source Presto as well as best of breed ISV products for fast, interactive, ad-hoc analytics use cases," HPE said in a blog post. "The Ampool team brings open source expertise and technology to provide a caching layer to address speed. The use of multiple ephemeral container-based SQL compute engines, such as Presto and Spark, introduces the need for persistent metadata to be stored and managed externally. Ampool has deep expertise in building a shared metadata catalog with role-based access control, which provides a consistent view of the different backend data sources."

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