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  • Workload management

    Discussion of workload management technology, typically in analytic or mixed-workload DBMS.

    June 8, 2015

    Teradata will support Presto

    At the highest level:

    Now let’s make that all a little more precise.

    Regarding Presto (and I got most of this from Teradata)::

    Daniel Abadi said that Presto satisfies what he sees as some core architectural requirements for a modern parallel analytic RDBMS project:? 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

    August 7, 2014

    Actian Vector Hadoop Edition

    I have a small blacklist of companies I won’t talk with because of their particularly unethical past behavior. Actian is one such; they evidently made stuff up about me that Josh Berkus gullibly posted for them, and I don’t want to have conversations that could be dishonestly used against me.

    That said, Peter Boncz isn’t exactly an Actian employee. Rather, he’s the professor who supervised Marcin Zukowski’s PhD thesis that became Vectorwise, and I chatted with Peter by Skype while he was at home in Amsterdam. I believe his assurances that no Actian personnel sat in on the call. ??

    In other news, Peter is currently working on and optimistic about HyPer. But we literally spent less than a minute talking about that

    Before I get to the substance, there’s been a lot of renaming at Actian. To quote Andrew Brust,

    … the ParAccel, Pervasive and?Vectorwise technologies are being unified under the Actian Analytics Platform brand.?Specifically, the ParAccel?technology … is being?re-branded?Actian Matrix; Pervasive’s?technologies are rechristened Actian DataFlow and Actian DataConnect; and Vectorwise becomes Actian Vector.

    and

    Actian … is now “one company, with one voice and one platform” according to its John Santaferraro

    The bolded part of the latter quote is untrue — at least in the ordinary sense of the word “one” — but the rest can presumably be taken as company gospel.

    All this is by way of preamble to saying that Peter reached out to me about Actian’s new Vector Hadoop Edition when he blogged about it last June, and we finally talked this week. Highlights include:? 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

    May 2, 2014

    Introduction to CitusDB

    One of my lesser-known clients is Citus Data, a largely Turkish company that is however headquartered in San Francisco. They make CitusDB, which puts a scale-out layer over a collection of fully-functional PostgreSQL nodes, much like Greenplum and Aster Data before it. However, in contrast to those and other Postgres-based analytic MPP (Massively Parallel Processing) DBMS:

    *One benefit to this strategy, besides the usual elasticity and recovery stuff, is that while PostgreSQL may be single-core for any given query, a CitusDB query can use multiple cores by virtue of hitting multiple PostgreSQL tables on each node.

    Citus has thrown a few things against the wall; for example, there are two versions of its product, one which involves HDFS (Hadoop Distributed File System) and one of which doesn’t. But I think Citus’ focus will be scale-out PostgreSQL for at least the medium-term future. Citus does have actual customers, and they weren’t all PostgreSQL users previously. Still, the main hope — at least until the product is more built-out — is that existing PostgreSQL users will find CitusDB easy to adopt, in technology and price alike.

    Read more

    May 1, 2014

    MemSQL update

    I stopped by MemSQL last week, and got a range of new or clarified information. For starters:

    On the more technical side: Read more

    April 30, 2014

    Cloudera, Impala, data warehousing and Hive

    There’s much confusion about Cloudera’s SQL plans and beliefs, and the company has mainly itself to blame. That said, here’s what I think is going on.

    And of course, as vendors so often do, Cloudera generally overrates both the relative maturity of Impala and the relative importance of the use cases in which its offerings – Impala or otherwise – shine.

    Related links

    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

    June 23, 2013

    Impala and Parquet

    I visited Cloudera Friday for, among other things, a chat about Impala with Marcel?Kornacker and colleagues. Highlights included:

    Data gets into Parquet via batch jobs only — one reason it’s important that Impala run against multiple file formats — but background format conversion is another roadmap item. A single table can be split across multiple formats — e.g., the freshest data could be in HBase, with the rest is in Parquet.

    Read more

    May 27, 2013

    IBM BLU

    I had a good chat with IBM about IBM BLU, aka BLU Accelerator or Acceleration. BLU basics start:

    And yes — that means Oracle is now the only major relational DBMS vendor left without a true columnar story.

    BLU’s maturity and scalability basics start:

    BLU technical highlights include: Read more

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