Data warehousing

Analysis of issues in data warehousing, with extensive coverage of database management systems and data warehouse appliances that are optimized to query large volumes of data. Related subjects include:

May 27, 2013

Data skipping

Way back in 2006, I wrote about a cool Netezza feature called the zone map, which in essence allows you to do partition elimination even in the absence of strict range partitioning.

Netezza’s substitute for range partitioning is very simple. Netezza features “zone maps,” which note the minimum and maximum of each column value (if such concepts are meaningful) in each extent. This can amount to effective range partitioning over dates; if data is added over time, there’s a good chance that the data in any particular date range is clustered, and a zone map lets you pick out which data falls in the desired data range.

I further wrote

… that seems to be the primary scenario in which zone maps confer a large benefit.

But I now think that part was too pessimistic. For example, in bulk load scenarios, it’s easy to imagine ways in which data can be clustered or skewed. And in such cases, zone maps can let you skip a large fraction of potential I/O.

Over the years I’ve said that other things were reminiscent of Netezza zone maps, e.g. features of Infobright, SenSage, InfiniDB and even Microsoft SQL Server. But truth be told, when I actually use the phrase “zone map”, people usually give me a blank look.

In a recent briefing about BLU, IBM introduced me to a better term — data skipping. I like it and, unless somebody comes up with a good reason not to, I plan to start using it myself. :)

April 25, 2013

Goodbye VectorWise, farewell ParAccel?

Actian, which already owns VectorWise, is also buying ParAccel. The argument for why this kills VectorWise is simple. ParAccel does most things VectorWise does, more or less as well. It also does a lot more:

One might conjecture that ParAccel is bad at highly concurrent, single-node use cases, and VectorWise is better at them — but at the link above, ParAccel bragged of supporting 5,000 concurrent connections. Besides, if one is just looking for a high-use reporting server, why not get Sybase IQ?? Anyhow, Actian hasn’t been investing enough in VectorWise to make it a major market player, and they’re unlikely to start now that they own ParAccel as well.

But I expect ParAccel to fail too. Reasons include:

Read more

April 15, 2013

Notes on Teradata systems

Teradata is announcing its new high-end systems, the Teradata 6700 series. Notes on that include:

Teradata is also talking about data integration and best-of-breed systems, with buzzwords such as:

Read more

April 15, 2013

Teradata SQL-H

As vendors so often do, Teradata has caused itself some naming confusion. SQL-H was introduced as a facility of Teradata Aster, to complement SQL-MR.* But while SQL-MR is in essence a set of SQL extensions, SQL-H is not. Rather, SQL-H is a transparency interface that makes Hadoop data responsive to the same code that would work on Teradata Aster …

*Speaking of confusion — Teradata Aster seems to use the spellings SQL/MR and SQL-MR interchangeably.

… except that now there’s also a SQL-H for regular Teradata systems as well. While it has the same general features and benefits as SQL-H for Teradata Aster, the details are different, since the underlying systems are.

I hope that’s clear. :)

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 26, 2013

Platfora at the time of first GA

Well-resourced Silicon Valley start-ups typically announce their existence multiple times. Company formation, angel funding, Series A funding, Series B funding, company launch, product beta, and product general availability may not be 7 different “news events”, but they’re apt to be at least 3-4. Platfora, no exception to this rule, is hitting general availability today, and in connection with that I learned a bit more about what they are up to.

In simplest terms, Platfora offers exploratory business intelligence against Hadoop-based data. As per last weekend’s post about exploratory BI, a key requirement is speed; and so far as I can tell, any technological innovation Platfora offers relates to the need for speed. Specifically, I drilled into Platfora’s performance architecture on the query processing side (and associated data movement); Platfora also brags of rendering 100s of 1000s of “marks” quickly in HTML5 visualizations, but I haven’t a clue as to whether that’s much of an accomplishment in itself.

Platfora’s marketing suggests it obviates the need for a data warehouse at all; for most enterprises, of course, that is a great exaggeration. But another dubious aspect of Platfora marketing actually serves to understate the product’s merits — Platfora claims to have an “in-memory” product, when what’s really the case is that Platfora’s memory-centric technology uses both RAM and disk to manage larger data marts than could reasonably be fit into RAM alone. Expanding on what I wrote about Platfora when it de-stealthedRead 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

February 13, 2013

It’s hard to make data easy to analyze

It’s hard to make data easy to analyze. While everybody seems to realize this — a few marketeers perhaps aside — some remarks might be useful even so.

Many different technologies purport to make data easy, or easier, to an analyze; so many, in fact, that cataloguing them all is forbiddingly hard. Major claims, and some technologies that make them, include:

*Complex event/stream processing terminology is always problematic.

My thoughts on all this start:  Read more

February 6, 2013

Key questions when selecting an analytic RDBMS

I recently complained that the Gartner Magic Quadrant for Data Warehouse DBMS conflates many use cases into one set of rankings. So perhaps now would be a good time to offer some thoughts on how to tell use cases apart. Assuming you know that you really want to manage your analytic database with a relational DBMS, the first questions you ask yourself could be:

Let’s drill down. Read more

February 5, 2013

Comments on Gartner’s 2012 Magic Quadrant for Data Warehouse Database Management Systems — evaluations

To my taste, the most glaring mis-rankings in the 2012/2013 Gartner Magic Quadrant for Data Warehouse Database Management are that it is too positive on Kognitio and too negative on Infobright. Secondarily, it is too negative on HP Vertica, and too positive on ParAccel and Actian/VectorWise. So let’s consider those vendors first.

Gartner seems confused about Kognitio’s products and history alike.

Gartner is correct, however, to note that Kognitio doesn’t sell much stuff overall.

* non-existent

In the cases of HP Vertica, Infobright, ParAccel, and Actian/VectorWise, the 2012 Gartner Magic Quadrant for Data Warehouse Database Management’s facts are fairly accurate, but I dispute Gartner’s evaluation. When it comes to Vertica: Read more

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