June 19, 2012

Notes on HBase 0.92

This is part of a four-post series, covering:

As part of my recent round of Hadoop research, I talked with Cloudera’s Todd Lipcon. Naturally, one of the subjects was HBase, and specifically HBase 0.92. I gather that the major themes to HBase 0.92 are:

HBase coprocessors are Java code that links straight into HBase. As with other DBMS extensions of the “links straight into the DBMS code” kind,* HBase coprocessors seem best suited for very sophisticated users and third parties.** Evidently, coprocessors have already been used to make HBase security more granular — role-based, per-column-family/per-table, etc. Further, Todd thinks coprocessors could serve as a good basis for future HBase enhancements in areas such as aggregation or secondary indexing. Read more

June 19, 2012

“Enterprise-ready Hadoop”

This is part of a four-post series, covering:

The posts depend on each other in various ways.

Cloudera, Hortonworks, and MapR all claim, in effect, “Our version of Hadoop is enterprise-ready, unlike those other guys’.” I’m dubious.

That said, “enterprise-ready Hadoop” really is an important topic.

So what does it mean for something to be “enterprise-ready”, in whole or in part? Common themes in distinguishing between “enterprise-class” and other software include:

For Hadoop, as for most things, these concepts overlap in many ways. Read more

November 12, 2011

Exasol update

I last wrote about Exasol in 2008. After talking with the team Friday, I’m fixing that now. :) The general theme was as you’d expect: Since last we talked, Exasol has added some new management, put some effort into sales and marketing, got some customers, kept enhancing the product and so on.

Top-level points included:

Read more

July 5, 2011

Eight kinds of analytic database (Part 2)

In Part 1 of this two-part series, I outlined four variants on the traditional enterprise data warehouse/data mart dichotomy, and suggested what kinds of DBMS products you might use for each. In Part 2 I’ll cover four more kinds of analytic database — even newer, for the most part, with a use case/product short list match that is even less clear.  Read more

July 5, 2011

Eight kinds of analytic database (Part 1)

Analytic data management technology has blossomed, leading to many questions along the lines of “So which products should I use for which category of problem?” The old EDW/data mart dichotomy is hopelessly outdated for that purpose, and adding a third category for “big data” is little help.

Let’s try eight categories instead. While no categorization is ever perfect, these each have at least some degree of technical homogeneity. Figuring out which types of analytic database you have or need — and in most cases you’ll need several — is a great early step in your analytic technology planning.  Read more

June 26, 2011

What to think about BEFORE you make a technology decision

When you are considering technology selection or strategy, there are a lot of factors that can each have bearing on the final decision — a whole lot. Below is a very partial list.

In almost any IT decision, there are a number of environmental constraints that need to be acknowledged. Organizations may have standard vendors, favored vendors, or simply vendors who give them particularly deep discounts. Legacy systems are in place, application and system alike, and may or may not be open to replacement. Enterprises may have on-premise or off-premise preferences; SaaS (Software as a Service) vendors probably have multitenancy concerns. Your organization can determine which aspects of your system you’d ideally like to see be tightly integrated with each other, and which you’d prefer to keep only loosely coupled. You may have biases for or against open-source software. You may be pro- or anti-appliance. Some applications have a substantial need for elastic scaling. And some kinds of issues cut across multiple areas, such as budget, timeframe, security, or trained personnel.

Multitenancy is particularly interesting, because it has numerous implications. Read more

June 20, 2011

The Vertica story (with soundbites!)

I’ve blogged separately that:

And of course you know:

Read more

February 5, 2011

Comments on the Gartner 2010/2011 Data Warehouse Database Management Systems Magic Quadrant

Edit: Comments on the February, 2012 Gartner Magic Quadrant for Data Warehouse Database Management Systems — and on the companies reviewed in it — are now up.

The Gartner 2010 Data Warehouse Database Management Systems Magic Quadrant is out. I shall now comment, just as I did to varying degrees on the 2009, 2008, 2007, and 2006 Gartner Data Warehouse Database Management System Magic Quadrants.

Note: Links to Gartner Magic Quadrants tend to be unstable. Please alert me if any problems arise; I’ll edit accordingly.

In my comments on the 2008 Gartner Data Warehouse Database Management Systems Magic Quadrant, I observed that Gartner’s “completeness of vision” scores were generally pretty reasonable, but their “ability to execute” rankings were somewhat bizarre; the same remains true this year. For example, Gartner ranks Ingres higher by that metric than Vertica, Aster Data, ParAccel, or Infobright. Yet each of those companies is growing nicely and delivering products that meet serious cutting-edge analytic DBMS needs, neither of which has been true of Ingres since about 1987.  Read more

February 2, 2011

Exadata notes

It’s been a while since I penetrated Oracle’s tight message control and actually talked with them about Exadata. But Doug Henschen wrote a good article about Exadata based on an Andy Mendelsohn webcast. I agree with almost all of it. At first I was a little surprised that Exadata’s emphasis shift from data warehousing to OLTP/generic consolidation hasn’t gone more quickly, but on the other hand:

Doug did overstate when he said that columnar architectures give 100X or more compression. That doesn’t happen. Yes, columnar compression can be >10X in a variety of use cases, while pre-Exadata Oracle index bloat can approach 10X at times; but even if you’re counting that way I doubt there are many instances in which it actually multiplies out to >100.

In other Exadata news, the long-standing observation that Oracle doesn’t like to do on-site Exadata POCs still holds true. A couple of existing Oracle users — one rather well-known — recently told me that Oracle won’t let them text Exadata except on Oracle premises. In one case, this is a deal-breaker keeping Exadata from being considered for a purchase, and Oracle still won’t budge.

Finally, I’m pretty sure that this “new” Softbank Teradata replacement Oracle has been touting since September as competitive evidence — which Doug’s article also references — isn’t quite what it sounds like. I believe Teradata’s version of the story, which somewhat edited goes like this:  Read more

January 18, 2011

Architectural options for analytic database management systems

Mike Stonebraker recently kicked off some discussion about desirable architectural features of a columnar analytic DBMS. Let’s expand the conversation to cover desirable architectural characteristics of analytic DBMS in general.  Read more

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