back to article Hadoop-flinger MapR: Yes to IPO, profits 'soon after'

MapR Technologies, a data management platform headquartered in San Jose, California, is going for IPO – but not yet, the company’s chief executive Matt Mills said today. Speaking to The Register in London, Mills said flotation is on the cards but declined to name a date. He joined MapR as president and chief operating office …

  1. Anonymous Coward
    Anonymous Coward

    "...relatively few customers’ Hadoop projects are making it into production."

    Eh, this is a myth. HDP and CLDR both have shedloads of customers running production workloads. Their big challenge is the cost of sale is off the charts so it takes 1-2 full subscription cycles to turn a profit, the whole while the customer could swan off somewhere else, like AWS.

    That said, MapR don't really compete with either company. MapR sell a proprietary storage product that has some (poorly implemented) overlap with Hadoop's APIs. They sell storage solutions to storage people and we all know where that market is going.

    MapR will have to IPO. They're out of money and their customer base is too small to sustain any investment. They're at the point now where they're just rebranding existing products into new architectures rather than innovating.

    1. Anonymous Coward
      Anonymous Coward

      @AC

      I have to post AC for the obvious reasons.

      Here is what I can say...

      1) A customer will run multiple projects on a cluster. (Multi-tenant)

      Not all of the development efforts will end up being used in production. Not all of the efforts pan out. This happens more than you would think. So while many customers are running production clusters... that doesn't mean there isn't a lot of R&D dollars spent that doesn't end up in a production app.

      2) Cost of sale...

      This is a relative thing. You want to compare apples to apples, so you need to look at the alternative major DW platforms like Oracle, IBM, and Teradata offer. Then look at the costs. Relative to that ... big data is cheaper. There's more and I could lecture you for hours on the business side of costs and why Cloudera and Hortonworks are still burning cash.

      3) MapR IPO.

      Yes it will happen. Probably sooner than you or the author think. Or it may be postponed based on the markets. MapR isn't running out of cash and it. Unlike Cloudera and Hortonworks which have tried to grab as much market share, MapR went long and slow.

      All three vendors have gaps in terms of product and deliverables. Yet MapR has something that neither have... proprietary software. While at first many ignored MapR because of this, not realizing the minute you chose a vendor, you weren't able to make any custom mods to things like HDFS , Hive, HBase and had to lock in to their track. (So you had to use the right supported version and wait for an official upgrade.)

      What gave MapR its advantage was / is the filesystem.

      But I digress.

      You clearly don't know Hadoop, or MapR as well as you think you do.

      Of the three. I'll wager that MapR has the stronger books.

      Bringing Mills on was mixed blessings. He's done some smart things, he's done some not so smart things and he and his crew brought some bad ideas from Oracle.

      1. Anonymous Coward
        Anonymous Coward

        Re: @AC

        "This is a relative thing. You want to compare apples to apples, so you need to look at the alternative major DW platforms like Oracle, IBM, and Teradata offer. Then look at the costs. Relative to that ... big data is cheaper. There's more and I could lecture you for hours on the business side of costs and why Cloudera and Hortonworks are still burning cash."

        Not sure about that if you are talking about "cost of sales". A lot of people just buy Oracle or IBM bc they have had it forever. Not, at this point, a very high cost of sales... relatively speaking as compared to the dollars they bring in. With the Hadoop people they have to do a lot of education and build an environment from scratch... and then they have to convince people they should not only do Hadoop but their flavor of it... and that they should do it on prem as opposed to AWS or GCP. I know you can run MapR in a cloud provider, but the cloud providers have their own managed Hadoop so unlikely.

      2. Anonymous Coward
        Anonymous Coward

        Re: @AC

        AC1 here.

        On point 1: this is the same as any other technology. However both HDP and CLDR growth is driven primarily by net-new use cases coming into production rather than new customer acquisition, which tends to be a (very) small initial purchase. The idea that "customers are struggling to get into production" is becoming less and less true as each quarter passes, particularly given how easy both companies have made it to run on cloud platforms (CLDR's IPO made much hay of having 30%+ of customers running on cloud infrastructure vs 18% for data in general). More customers are getting more workloads into production all the time, and both companies sport well over 1,000 customers each, admittedly with some overlap - particularly in FS.

        Point 2: I was talking about cost of sale for CLDR and HDP. Selling an RDBMS or cloud is pretty easy. Customers don't need much education before you can start making money from them. Selling big data stacks is hard. Customers need education, training and barely-profitable services to be successful. I'm in absolute agreement that big data platforms are both substantially cheaper to run and deliver orders of magnitude greater capability.

        Point 3: MapRFS has proven to be an enormous disadvantage in reality. It has no functional advantages, and hasn't for well over three years. That leaves it as what it is - a niche, storage-centric product onto which Hadoop ecosystem clones have been bolted on. It costs MapR an enormous amount of cash to keep those cloned APIs up to date (something they barely manage) and it utterly muddies the water for customers as to which bits they can use - the open source stack or MapR's (allegedly) compatible proprietary clone. It's no doubt technically interesting, but that neither leads to success nor makes money. The immediate business disadvantage for MapR is the cost of supporting such an obscene number of products. They simply can't do it with the cash they have/used to have on hand, borne out in a raft of analyst reports and customer gossip.

        As an aside, CLDR these days mostly market their proprietary software, of which they have plenty (labelled in the IPO pitch as "HOSS" - hybrid open source). Even HDP, as much as they may be loathe to admit it, sell plenty of it. Can't exactly do a git clone on Cloudbreak or AtScale now, can you?

        For me the proof is in the pudding. MapR are nonexistant in EMEA, APJ or China. They're nonexistant on the cloud. You can't survive like that, and that's more than clear in their recent announcements. HDP have just wrapped up a huge investment in LLAP, CLDR in their own PaaS (following on rapidly from Kudu). MapR? A "Cloud Scale Data Store" built on "Converge-X Data Fabric". What does that mean? MapR FS with a new label, targeting the converged storage use case.

        Best case for MapR would be acquisition, but that ship sailed years ago. Only option now is a mid-sized IPO and a pure focus on the storage use case, and hope AMEX don't stop being a customer before they turn a profit. They'd be truly fucked if they lost that little cashcow.

    2. Anonymous Coward
      Anonymous Coward

      "the customer could swan off somewhere else, like AWS."

      True, that is the issue for these managed Hadoop environments. Hadoop is a perfect workload (highly variable utilization) to run in the public cloud. AWS and Google Cloud both have their own services which get around all these managed providers. Hadoop is based on Google tech, GFS and so forth, (expanded by Yahoo) so they probably know how to run it pretty well.

      There are plenty of Hadoop implementations out there. Probably shouldn't be as most of these people are just trying to scale storage, and not pay NetApp, or scale a data warehouse, and not pay Oracle. Probably easier ways to go about it, i.e. Dremel with some cloud object store.

  2. Anonymous Coward
    Anonymous Coward

    Anonymously people, your views are crap unless you say who you work for.

    I would say 99% of you work for either the vendor in the article or their competition.

    Both of which negate your comments.

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