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  • April 17, 2017

    Interana

    Interana has an interesting story, in technology and business model alike. For starters:

    And to be clear — if we leave aside any questions of marketing-name sizzle, this really is business intelligence. The closest Interana comes to helping with predictive modeling is giving its ad-hoc users inspiration as to where they should focus their modeling attention.

    Interana also has an interesting twist in its business model, which I hope can be used successfully by other enterprise software startups as well. Read more

    December 7, 2015

    Transitioning to the cloud(s)

    There’s a lot of talk these days about transitioning to the cloud, by IT customers and vendors alike. Of course, I have thoughts on the subject, some of which are below.

    1. The economies of scale of not running your own data centers are real. That’s the kind of non-core activity almost all enterprises should outsource. Of course, those considerations taken alone argue equally for true cloud, co-location or SaaS (Software as a Service).

    2. When the (Amazon) cloud was newer, I used to hear that certain kinds of workloads didn’t map well to the architecture Amazon had chosen. In particular, shared-nothing analytic query processing was necessarily inefficient. But I’m not hearing nearly as much about that any more.

    3. Notwithstanding the foregoing, not everybody loves Amazon pricing.

    4. Infrastructure vendors such as Oracle would like to also offer their infrastructure to you in the cloud. As per the above, that could work. However:

    Actually, if we replace “Oracle” by “Microsoft”, the whole idea sounds better. While Microsoft doesn’t have a proprietary server hardware story like Oracle’s, many folks are content in the Microsoft walled garden. IBM has fiercely loyal customers as well, and so may a couple of Japanese computer manufacturers.

    5. Even when running stuff in the cloud is otherwise a bad idea, there’s still: Read more

    October 26, 2015

    Differentiation in business intelligence

    Parts of the business intelligence differentiation story resemble the one I just posted for data management. After all:

    That said, insofar as BI’s competitive issues resemble those of DBMS, they are those of DBMS-lite. For example:

    And full-stack analytic systems — perhaps delivered via SaaS (Software as a Service) — can moot the BI/data management distinction anyway.

    Of course, there are major differences between how DBMS and BI are differentiated. The biggest are in user experience. I’d say: Read more

    October 26, 2015

    Differentiation in data management

    In the previous post I broke product differentiation into 6-8 overlapping categories, which may be abbreviated as:

    and sometimes also issues in adoption and administration.

    Now let’s use this framework to examine two market categories I cover — data management and, in separate post, business intelligence.

    Applying this taxonomy to data management:
    Read more

    October 26, 2015

    Sources of differentiation

    Obviously, a large fraction of what I write about involves technical differentiation. So let’s try for a framework where differentiation claims can be placed in context. This post will get through the generalities. The sequels will apply them to specific cases.

    Many buying and design considerations for IT fall into six interrelated areas:? Read more

    October 15, 2015

    Basho and Riak

    Basho was on my (very short) blacklist of companies with whom I refuse to speak, because they have lied about the contents of previous conversations. But Tony Falco et al. are long gone from the company. So when Basho’s new management team reached out, I took the meeting.

    For starters:

    Basho’s product line has gotten a bit confusing, but as best I understand things the story is:

    Technical notes on some of that include:? Read more

    September 17, 2015

    Rocana’s world

    For starters:

    Rocana portrays itself as offering next-generation IT operations monitoring software. As you might expect, this has two main use cases:

    Rocana’s differentiation claims boil down to fast and accurate anomaly detection on large amounts of log data, including but not limited to:

    Read more

    June 10, 2015

    Hadoop generalities

    Occasionally I talk with an astute reporter — there are still a few left ?? — and get led toward angles I hadn’t considered before, or at least hadn’t written up. A blog post may then ensue. This is one such post.

    There is a group of questions going around that includes:

    To a first approximation, my responses are:? Read more

    May 20, 2015

    MemSQL 4.0

    I talked with my clients at MemSQL about the release of MemSQL 4.0. Let’s start with the reminders:

    The main new aspects of MemSQL 4.0 are:

    There’s also a new free MemSQL “Community Edition”. MemSQL hopes you’ll experiment with this but not use it in production. And MemSQL pricing is now wholly based on RAM usage, so the column store is quasi-free from a licensing standpoint is as well.

    Read more

    February 18, 2015

    Greenplum is being open sourced

    While I don’t find the Open Data Platform thing very significant, an associated piece of news seems cooler — Pivotal is open sourcing a bunch of software, with Greenplum as the crown jewel. Notes on that start:

    Greenplum, let us recall, is a pretty decent MPP (Massively Parallel Processing) analytic RDBMS. Various aspects of it were oversold at various times, and I’ve never heard that they actually licked concurrency. But Greenplum has long had good SQL coverage and petabyte-scale deployments and a columnar option and some in-database analytics and so on; i.e., it’s legit. When somebody asks me about open source analytic RDBMS to consider, I expect Greenplum to consistently be on the short list.

    Further, the low-cost alternatives for analytic RDBMS are adding up. Read more

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