Hewlett Packard Enterprise Inc. said today it will acquire the assets of MapR Technologies Inc. for an undisclosed sum, ending a two-month drama that cast a harsh light on the struggles of once high-flying big-data companies.

HPE said the deal, which was announced this morning, includes MapR’s technology, intellectual property and expertise in artificial intelligence and data management. The company didn’t specify how many people would come with the deal, but “our intent is to have a large number of employees join us,” said Patrick Osborne, vice president of big data and secondary storage at HPE.

Existing MapR customers will continue to be supported along with ongoing renewals, HPE said. HPE didn’t mention MapR’s legacy Hadoop business as a factor in its decision, but it intends to support those customers indefinitely as well, Osborne said. “We want to maximize customer retention,” he said. “Some of those customers started with [the Hadoop HDFS file system] and have moved into streaming and are now extending to AI and machine learning. From our perspective the market is expanding.”

The MapR technology will be folded into HPE’s Intelligent Data Platform, a set of technologies for data lifecycle management. MapR’s distributed file system “provides the capability of a data fabric that allows people to manage their analytics on the edge as well as in the core,” Osborne said. “We didn’t have a technology that would allow customers to do that.” MapR’s technology for persistent container storage, data lakes and streaming data were particularly attractive, he said.

The two companies have been partners for several years and have many customers in common, Osborne said. “This was a chance to continue the journey with their customers, particularly in industries that are being transformed by analytics and AI,” he said. HPE also praised MapR’s ecosystem of resellers, software partners and integrators, which it said will be selectively folded into its own partner network.

Analysts praised the deal. “MapR’s technologies and team are top-notch, and they will be an excellent addition to the HPE family going forward,” said James Kobielus, lead AI and data science analyst at Wikibon, the sister market research company of SiliconANGLE.

HPE said MapR’s technology will be particularly valuable in helping customers stitch together data pipelines across multiple on-premises and cloud environments as well as to run multiple workloads in the same environment. MapR has recently been positioning its technology as a single platform for integrating multiple data sources after pivoting from its origins as a seller of services billed upon the Hadoop big data platform.

“MapR had clearly built up a substantial portfolio of intellectual property for real-time, streaming and edge use cases,” said Kobielus said. “This is a smart move by HPE to bring mature assets into its cloud-to-edge portfolio, while providing MapR’s customers with the assurance that their investments are safe.”

Wikibon Chief Analyst David Vellante agreed. “MapR has good technology; their file system and database are world class and HPE needs the IP,” he said, adding, “I’m sure they picked this up for a good price.”

The deal brings to an end a soap opera that began in late May with MapR’s bombshell announcement that it may be forced to shut down the company after “extremely poor results” in the most recent fiscal quarter. The company set a self-imposed July 3 deadline to find a funding source, but as that date came and went, the company would only state that it was “making meaningful progress toward a strategic transaction.”

MapR was one of three high-profile startups, along with Cloudera Inc. and Hortonworks Inc., that collectively raised more than $1.5 billion in funding in the heady early days of the big data movement. Its CEO publicly announced plans for an initial public offering in 2015, but customers’ faster-than-expected move to the cloud, combined with the market’s overall ebbing interest in Hadoop, sent the fortunes of all three companies spiraling downward shortly thereafter.

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