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  • HP and Neoview

    Discussion of computer giant HP, especially its efforts in data warehousing and business intelligence. Covered are both HP’s own data warehouse appliance Neoview and its partnerships with other software vendors. Related subjects include:

    August 28, 2016

    Are analytic RDBMS and data warehouse appliances obsolete?

    I used to spend most of my time — blogging and consulting alike — on data warehouse appliances and analytic DBMS. Now I’m barely involved with them. The most obvious reason is that there have been drastic changes in industry structure:

    Simply reciting all that, however, begs the question of whether one should still care about analytic RDBMS at all.

    My answer, in a nutshell, is:

    Analytic RDBMS — whether on premises in software, in the form of data warehouse appliances, or in the cloud — are still great for hard-core business intelligence, where “hard-core” can refer to ad-hoc query complexity, reporting/dashboard concurrency, or both. But they aren’t good for much else.

    Read more

    March 10, 2015

    Notes on HBase

    I talked with a couple of Cloudera folks about HBase last week. Let me frame things by saying:

    Also:

    Read more

    December 7, 2014

    Notes on the Hortonworks IPO S-1 filing

    Given my stock research experience, perhaps I should post about Hortonworks’ initial public offering S-1 filing. ?? For starters, let me say:

    And, perhaps of interest only to me — there are approximately 50 references to YARN in the Hortonworks S-1, but only 1 mention of Tez.

    Read more

    September 7, 2014

    An idealized log management and analysis system — from whom?

    I’ve talked with many companies recently that believe they are:

    At best, I think such competitive claims are overwrought. Still, it’s a genuinely important subject and opportunity, so let’s consider what a great log management and analysis system might look like.

    Much of this discussion could apply to machine-generated data in general. But right now I think more players are doing product management with an explicit conception either of log management or event-series analytics, so for this post I’ll share that focus too.

    A short answer might be “Splunk, but with more analytic functionality and more scalable performance, at lower cost, plus numerous coupons for free pizza.” A more constructive and bottoms-up approach might start with:? Read more

    July 14, 2014

    21st Century DBMS success and failure

    As part of my series on the keys to and likelihood of success, I outlined some examples from the DBMS industry. The list turned out too long for a single post, so I split it up by millennia. The part on 20th Century DBMS success and failure went up Friday; in this one I’ll cover more recent events, organized in line with the original overview post. Categories addressed will include analytic RDBMS (including data warehouse appliances), NoSQL/non-SQL short-request DBMS, MySQL, PostgreSQL, NewSQL and Hadoop.

    DBMS rarely have trouble with the criterion “Is there an identifiable buying process?” If an enterprise is doing application development projects, a DBMS is generally chosen for each one. And so the organization will generally have a process in place for buying DBMS, or accepting them for free. Central IT, departments, and — at least in the case of free open source stuff — developers all commonly have the capacity for DBMS acquisition.

    In particular, at many enterprises either departments have the ability to buy their own analytic technology, or else IT will willingly buy and administer things for a single department. This dynamic fueled much of the early rise of analytic RDBMS.

    Buyer inertia is a greater concern.

    A particularly complex version of this dynamic has played out in the market for analytic RDBMS/appliances.

    Otherwise I’d say:? Read more

    December 5, 2013

    Vertica 7

    It took me a bit of time, and an extra call with Vertica’s long-time R&D chief Shilpa Lawande, but I think I have a decent handle now on Vertica 7, code-named Crane. The two aspects of Vertica 7 I find most interesting are:

    Other Vertica 7 enhancements include:

    Overall, two recurring themes in our discussion were:

    Read more

    November 29, 2013

    SaaS appliances, SaaS data centers, and customer-premises SaaS

    Conclusions

    I think that most sufficiently large enterprise SaaS vendors should offer an appliance option, as an alternative to the core multi-tenant service. In particular:

    How I reached them

    Core reasons for selling or using SaaS (Software as a Service) as opposed to licensed software start:

    Conceptually, then, customer-premises SaaS is not impossible, even though one of the standard Big Three SaaS benefits is lost. Indeed:

    But from an enterprise standpoint, that’s all (relatively) simple stuff. So we’re left with a more challenging question — does customer-premises SaaS make sense in the case of enterprise applications or other server software?

    Read more

    August 25, 2013

    Cloudera Hadoop strategy and usage notes

    When we scheduled a call to talk about Sentry, Cloudera’s Charles Zedlewski and I found time to discuss other stuff as well. One interesting part of our discussion was around the processing “frameworks” Cloudera sees as most important.

    HBase was artificially omitted from this “frameworks” discussion because Cloudera sees it as a little bit more of a “storage” system than a processing one.

    Another good subject was offloading work to Hadoop, in a couple different senses of “offload”: Read more

    July 2, 2013

    Notes and comments, July 2, 2013

    I’m not having a productive week, part of the reason being a hard drive crash that took out early drafts of what were to be last weekend’s blog posts. Now I’m operating from a laptop, rather than my preferred dual-monitor set-up. So please pardon me if I’m concise even by comparison to my usual standards.

    *Basic and unavoidable ETL (Extract/Transform/Load) of course excepted.

    **I could call that ABC (Always Be Comparing) or ABT (Always Be Testing), but they each sound like – well, like The Glove and the Lions.

    June 10, 2013

    Where things stand in US government surveillance

    Edit: Please see the comment thread below for updates. Please also see a follow-on post about how the surveillance data is actually used.

    US government surveillance has exploded into public consciousness since last Thursday. With one major exception, the news has just confirmed what was already thought or known. So where do we stand?

    My views about domestic data collection start:

    *Recall that these comments are US-specific. Data retention legislation has been proposed or passed in multiple countries to require recording of, among other things, all URL requests, with the stated goal of fighting either digital piracy or child pornography.

    As for foreign data: Read more

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