HPE plus MapR: Too much Hadoop, not enough cloud


Cloud killed the fortunes of their Hadoop trinity–Cloudera, Hortonworks, and MapR–and that same cloud likely won’t rain victory down HPE, which recently acquired the business assets of MapR. Though the arrangement promises to marry”MapR’s technology, intellectual property, and domain expertise in artificial intelligence and machine learning (AI/ML) and analytics information management” using HPE’s”Intelligent Data Platform capabilities,” the bargain is devoid of the 1 ingredient that both companies desire most: Cloud.

The problem, in other words, isn’t that MapR was not filled to the brim with smart folks and fantastic technology, as Wikibon analyst James Kobielus claims . No, the problem is that MapR is still way too Hadoop-y rather than nearly cloudy enough in a world filled with”fully integrated [cloud-first] offerings that have a lower cost of acquisition and are more economical to scale,” as Diffblue CEO Mathew Lodge has said. In short, MapR may expand HPE’s information resources, but it does not make HPE a cloud contender.

Why cloud issues

Yes, hybrid is still a thing, and will remain so for many years to come. As much as businesses may want to maneuver workloads into a cloudy future, 95 percent of IT remains firmly planted in private information centres. New workloads tend to proceed cloud, but there are literally decades of workloads still running on-premises.

But this hybrid world, which HPE pitches so loudly (“invention with hybrid cloud,””from border to blur,””harness the power of information where it lives,” etc.), hasn’t been as big a deal in big data workloads. Part of the reason comes down to some reliance on old-school models such as Hadoop,”built to be a giant sole source of information,” as noted by Amalgam Insights CEO Hyoun Park. That is a cumbersome model, especially in a world where big data is born in the cloud and wishes to stay there, instead of being sent to on-premises servers. Can you operate Hadoop in the cloud? Obviously. Companies like AWS do exactly that (Elastic MapReduce, anyone?) . But arguably even Hadoop from the cloud is a losing strategy for many big data workloads, because it simply does not match the streaming data world in which we live.

And then there is the on-premises problem. As AWS data science chief Matt Wood told me, cloud elasticity Is Essential to doing data science right:

Those that go out and buy expensive infrastructure find that the problem scope and domain change really quickly. By the time they get around to answering the initial question, the business has proceeded. You want an environment that is flexible and allows you to quickly react to changing big data requirements. Your source mix is continually evolving–if you buy infrastructure, it is almost immediately irrelevant to your business because it’s frozen in time. It is solving a problem you may not need or care about any longer.

MapR had made efforts to move beyond its on-premises Hadoop past, but arguably too little, too late.

Brother, can you spare a cloud?

Which brings us back to HPE. In 2015 the company dumped its public cloud offering, instead deciding to”double-down on our private and cloud capabilities” That may have seemed acceptable back when OpenStack was still breathing, but it pigeon-holed HPE as a mostly on-premises seller trying to partner its way to public cloud value. It is not enough.

Whereas Red Hat, by way of example, can credibly claim to possess deep assets in Kubernetes (Red Hat OpenShift) that help businesses build for hybrid vehicle and multi-cloud scenarios, HPE doesn’t. It’s tried to get there through purchase (e.g., BlueData for containers), but it simply lacks a cohesive product set.

More worryingly, every significant public cloud seller now has a good hybrid cloud offering, and ventures considering modernizing will frequently choose to choose the cloud-first vendor which also has expertise in private information centres, rather than betting on legacy vendors with ambitions for public cloud value. For Google, it is Anthos. For Microsoft Azure, hybrid vehicle was central to the company’s product offering and promotion from the beginning. And for AWS, which at one time eschewed private information centres, the company has built out a slew of hybrid services (e.g., Snowball) and partnerships (VMware) to assist enterprises have their cloud cake and eat private data centers, also.

Enter MapR, using its contrarian, proprietary method of the open source Hadoop marketplace. That approach won it several key converts, but it never needed a broad-based following. Fantastic tech? Sure. Cloudy DNA and goods? Nope.

In sum, although I expect the marriage of HPE and MapR will yield happy, cloudy enterprise clients, this”doubling-down” by HPE on technology assets that keep it firmly grounded on-premises doesn’t hold much promise. Big info belongs in the cloud, and cloud isn’t something you can buy. It’s a different way of working, another way of thinking. HPE didn’t get that DNA with MapR.

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