February 11, 2011

Comments on the 2011 Forrester Wave for Enterprise Data Warehouse Platforms

The Forrester Wave: Enterprise Data Warehouse Platforms, Q1 2011 is now out,* hot on the heels of the Gartner Magic Quadrant. Unfortunately, this particular Forrester Wave is riddled with inaccuracy. 

*At the time of this writing, I don’t have a link to a free version of the full report. At the time of this writing, the 2011 Forrester Wave for Enterprise Data Warehouse Platforms graphic can be found here.

One example of the confusion pervading the 2011 Forrester Wave for Enterprise Data Warehouse Platforms lies in a list of three supposed trends.

Some of the sillier specific claims in the Forrester Wave for Enterprise Data Warehouse Platforms include:

Even leaving aside the errors that obviously riddled the Forrester Wave for Enterprise Data Warehouse Platforms’ underlying 56-row matrix, I dispute the whole premise of the exercise. I’m not a big fan of overarching scorecard-based rankings, because the right choice of product varies so much by use case. For example:

More excusable is some terminological confusion in the Forrester Wave for Enterprise Data Warehouse Platforms, the essence of which is this:

Notwithstanding its name, the Forrester Wave for Enterprise Data Warehouse Platforms isn’t just talking about what are called enterprise data warehouses (EDWs), but rather a broader range of analytic database management systems and use cases. These include:

Indeed, the definition provided of “EDW” basically boils down to “runs SQL, is tuned in some way for analytics, has a cost-based or other query optimizer, and isn’t tied to a specific application.”

Frankly, I think classical EDWs have their problems, and are not necessarily the best way to address the numerous use cases for analytic DBMS technology. And product category names are commonly problematic anyhow. So I don’t much mind this overloading of the EDW term. But in one respect I think the Forrester Wave overdoes its inclusiveness — it includes things that aren’t actually DBMS, and then marks down just about every product cited for being a real DBMS rather than some sort of above-DBMS layer, at least when those things are sold by SAP. I’ve never agreed with the idea that SAP’s BW/BWA products should be included in a comparison with the other products cited in the Forrester Wave at all, and SAP HANA doesn’t change my mind.

One last thing — I’m suspicious of the Forrester Wave for Enterprise Data Warehouse Platforms’ comments on data warehouse appliance prices. However, they are hard to judge without knowing whether Forrester was using the term “raw data” in its usual sense, or actually means “user data”, and also without knowing whether Forrester is talking about list or “street” pricing.

Comments

8 Responses to “Comments on the 2011 Forrester Wave for Enterprise Data Warehouse Platforms”

  1. Alistair McEwan on February 15th, 2011 10:02 am

    Curt,
    I agree that the term “EDW” is blurry. Somewhere, I’ve read “EDW = RDBMS + X” whereby X constitutes all the code like extraction programs, scheduling scripts, SQL generated by modeling tools, ETL tool etc. This sounds to me a valid perspective. Gartner, Forrester and yourself seem to focus heavily on the RDBMS piece in that equation, basically “EDW = RDBMS”, which then leads to the question “What the heck? They are only discussing databases and SQL. So what?”. While an RDBMS plays a significant role in an EDW context I argue that an RDBMS is commodity and thus replaceable. It is the “X portion” that is pretty decisive. But that’s too proprietary and not generic enough for analysts. That’s why it gets discarded. But the real-world is different.

    Alistair

  2. Curt Monash on February 15th, 2011 11:31 am

    Alistair,

    That sounds like you’re saying RDBMS work well and hence are commodities, while ETL doesn’t work well and hence is the interesting part. There’s certainly some truth in that direction.

    But while RDBMS for handling traditional business-transaction data may be approaching commodity status, there’s a whole lot else RDBMS can do too, and that turns out not to have been commoditized yet at all.

    And even the parts that you might reasonably call “commodity”? As long as one pays Oracle prices for it, that’s not a commodity at all.

  3. Neil Raden on March 2nd, 2011 2:58 pm

    Curt,

    As usual, in awe of your ability to distill a ton complicated concepts and keep the other analysts honest. In defense of Forrester, it’s a hell of a hard job to produce all of this in a market that is so murky. Well done and thanks for the insights, I’ll now go and make money on them! LOL

    -NR

  4. Comments on the 2012 Forrester Wave: Enterprise Hadoop Solutions : DBMS 2 : DataBase Management System Services on February 6th, 2012 12:16 am

    [...] Forrester Waves always seem to have weird implicit definitions of “data warehousing”. This one is no exception. [...]

  5. Comments on the analytic DBMS industry and Gartner’s Magic Quadrant for same : DBMS 2 : DataBase Management System Services on February 9th, 2012 4:20 am

    [...] Whatever the problems may be with Gartner’s approach, the whole thing comes out better than do Forrester’s failed imitations. [...]

  6. John on February 9th, 2012 8:48 am

    Hi

    I would question some of what you are saying. Whilst Terradata is widely used and proven, I would say that one problem as with all MPP systems is that the front-end node becomes a bottleneck especially when a query that does not match the partitioning is run. This happens on Netezza and Greenplum also.

    Also from a support point of view I would say Sybase IQ is by far the lowest and I’ve also used the likes of Greenplum and Netezza to compare.

    I would question that Sybase IQ is not scaleable. In my experience it is highly scaleable and can grow to Petabytes of data and has massive performance scaleability.

  7. Curt Monash on February 9th, 2012 11:57 am

    Hi, John!

    Please do tell more about multi-petabyte Sybase IQ installations! The company itself has never mentioned a single one to me.

    Anyhow, I don’t hear a lot about head-node-style bottlenecks for Teradata query processing.

  8. Pivotal GPDB and the 2013 Forrester Wave EDW Report | Database Fog Blog on December 18th, 2013 3:26 pm

    [...] for bloggers when they report on the EDW space (see Curt Monash’s review of their last report here). They have a 2013 report out now that is quite mysterious (see [...]

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