m5彩票|平台登录

                                                    MarkLogic

                                                    Analysis of Mark Logic and its Marklogic Server search-friendly XML DBMS product. Related subjects include:

                                                    December 10, 2015

                                                    Readings in Database Systems

                                                    Mike Stonebraker and Larry Ellison have numerous things in common. If nothing else:

                                                    I mention the latter because there’s a new edition of Readings in Database Systems, aka the Red Book, available online, courtesy of Mike, Joe Hellerstein and Peter Bailis. Besides the recommended-reading academic papers themselves, there are 12 survey articles by the editors, and an occasional response where, for example, editors disagree. Whether or not one chooses to tackle the papers themselves — and I in fact have not dived into them — the commentary is of great interest.

                                                    But I would not take every word as the gospel truth, especially when academics describe what they see as commercial market realities. In particular, as per my quip in the first paragraph, the data warehouse market has not yet gone to the extremes that Mike suggests,* if indeed it ever will. And while Joe is close to correct when he says that the company Essbase was acquired by Oracle, what actually happened is that Arbor Software, which made Essbase, merged with Hyperion Software, and the latter was eventually indeed bought by the giant of Redwood Shores.**

                                                    *When it comes to data warehouse market assessment, Mike seems to often be ahead of the trend.

                                                    **Let me interrupt my tweaking of very smart people to confess that my own commentary on the Oracle/Hyperion deal was not, in retrospect, especially prescient.

                                                    Mike pretty much opened the discussion with a blistering attack against hierarchical data models such as JSON or XML. To a first approximation, his views might be summarized as:? Read more

                                                    October 15, 2015

                                                    Couchbase 4.0 and related subjects

                                                    I last wrote about Couchbase in November, 2012, around the time of Couchbase 2.0. One of the many new features I mentioned then was secondary indexing. Ravi Mayuram just checked in to tell me about Couchbase 4.0. One of the important new features he mentioned was what I think he said was Couchbase’s “first version” of secondary indexing. Obviously, I’m confused.

                                                    Now that you’re duly warned, let me remind you of aspects of Couchbase timeline.

                                                    Technical notes on Couchbase 4.0 — and related riffs ?? — start: 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

                                                    November 8, 2013

                                                    Comments on the 2013 Gartner Magic Quadrant for Operational Database Management Systems

                                                    The 2013 Gartner Magic Quadrant for Operational Database Management Systems is out. “Operational” seems to be Gartner’s term for what I call short-request, in each case the point being that OLTP (OnLine Transaction Processing) is a dubious term when systems omit strict consistency, and when even strictly consistent systems may lack full transactional semantics. As is usually the case with Gartner Magic Quadrants:

                                                    Anyhow:? Read more

                                                    April 1, 2013

                                                    Some notes on new-era data management, March 31, 2013

                                                    Hmm. I probably should have broken this out as three posts rather than one after all. Sorry about that.

                                                    Performance confusion

                                                    Discussions of DBMS performance are always odd, for starters because:

                                                    But in NoSQL/NewSQL short-request processing performance claims seem particularly confused. Reasons include but are not limited to:

                                                    MongoDB and 10gen

                                                    I caught up with Ron Avnur at 10gen. Technical highlights included: Read more

                                                    March 18, 2013

                                                    DBMS development and other subjects

                                                    The cardinal rules of DBMS development

                                                    Rule 1: Developing a good DBMS requires 5-7 years and tens of millions of dollars.

                                                    That’s if things go extremely well.

                                                    Rule 2: You aren’t an exception to Rule 1.?

                                                    In particular:

                                                    DBMS with Hadoop underpinnings …

                                                    … aren’t exceptions to the cardinal rules of DBMS development. That applies to Impala (Cloudera), Stinger (Hortonworks), and Hadapt, among others. Fortunately, the relevant vendors seem to be well aware of this fact. Read more

                                                    February 21, 2013

                                                    One database to rule them all?

                                                    Perhaps the single toughest question in all database technology is: Which different purposes can a single data store serve well? — or to phrase it more technically — Which different usage patterns can a single data store support efficiently? Ted Codd was on multiple sides of that issue, first suggesting that relational DBMS could do everything and then averring they could not. Mike Stonebraker too has been on multiple sides, first introducing universal DBMS attempts with Postgres and Illustra/Informix, then more recently suggesting the world needs 9 or so kinds of database technology. As for me — well, I agreed with Mike both times. ??

                                                    Since this is MUCH too big a subject for a single blog post, what I’ll do in this one is simply race through some background material. To a first approximation, this whole discussion is mainly about data layouts — but only if we interpret that concept broadly enough to comprise:

                                                    To date, nobody has ever discovered a data layout that is efficient for all usage patterns. As a general rule, simpler data layouts are often faster to write, while fancier ones can boost query performance. Specific tradeoffs include, but hardly are limited to: Read more

                                                    March 31, 2012

                                                    Our clients, and where they are located

                                                    From time to time, I disclose our vendor client lists. Another iteration is below, the first since a little over a year ago. To be clear:

                                                    For reasons explained below, I’ll group the clients geographically. Obviously, companies often have multiple locations, but this is approximately how it works from the standpoint of their interactions with me. Read more

                                                    January 8, 2012

                                                    Big data terminology and positioning

                                                    Recently, I observed that Big Data terminology is seriously broken. It is reasonable to reduce the subject to two quasi-dimensions:

                                                    given that

                                                    But the conflation should stop there.

                                                    *Low-volume/high-velocity problems are commonly referred to as “event processing” and/or “streaming”.

                                                    When people claim that bigness and structure are the same issue, they oversimplify into mush. So I think we need four pieces of terminology, reflective of a 2×2 matrix of possibilities. For want of better alternatives, my suggestions are:

                                                    Read more

                                                    November 3, 2011

                                                    MarkLogic’s Hadoop connector

                                                    It’s time to circle back to a subject I skipped when I otherwise wrote about MarkLogic 5: MarkLogic’s new Hadoop connector.

                                                    Most of what’s confusing about the MarkLogic Hadoop Connector lies in two pairs of options it presents you:

                                                    Otherwise, the whole thing is just what you would think:

                                                    MarkLogic said that it wrote this Hadoop connector itself.

                                                    Read more

                                                    Next Page →

                                                    Feed: DBMS (database management system), DW (data warehousing), BI (business intelligence), and analytics technology Subscribe to the Monash Research feed via RSS or email:

                                                    Login

                                                    Search our blogs and white papers

                                                    Monash Research blogs

                                                    User consulting

                                                    Building a short list? Refining your strategic plan? We can help.

                                                    Vendor advisory

                                                    We tell vendors what's happening -- and, more important, what they should do about it.

                                                    Monash Research highlights

                                                    Learn about white papers, webcasts, and blog highlights, by RSS or email.

                                                                                                      education

                                                                                                      image

                                                                                                      Buy a car

                                                                                                      Information

                                                                                                      news

                                                                                                      culture

                                                                                                      Go abroad

                                                                                                      Application Essentials

                                                                                                      Buddhism