Xtreme Data readies a different kind of FPGA-based data warehouse appliance

Xtreme Data called me to talk about its plans in the data warehouse appliance business, almost all details of which are currently embargoed. Still, a few points may be worth noting ahead of more precise information, namely:

• Xtreme Data’s basic idea is to take a custom board and build a data warehouse appliance around it.
• An Xtreme Data board looks a lot like a conventional two-socket board, but has only one four-core CPU. In addition, it sports some FPGAs (Field-Programmable Gate Arrays).
• In the Xtreme Data appliance, the FPGAs will be used for core SQL processing, after the data is ingested via conventional I/O. This is different from Netezza’s approach to FPGA-based data warehouse appliances, in which the FPGA sits in the place of a disk controller and touches the data first, before passing it off to a more or less conventional CPU.
• While preparing entry into the data warehouse appliance business, Xtreme Data has sold its board to 150 other outfits, many quite impressive. Buyers seem to be FPGA users who previously had to craft their own custom boards. According to Xtreme Data, major uses by these customers include:
  • Military/intelligence/digital signal processing.
  • Military/intelligence/cybersecurity (a newish area for Xtreme Data)
  • Bioinformatics/high-throughput gene sequencing (a “handful” of customers)
  • Medical imaging
  • More or less pure university research of various sorts (around 50 customers)
  • … but not database management.
• Xtreme Data’s website has a non-obvious URL.

So far as I can tell, Xtreme Data’s 1.0 product will — like most other 1.0 analytic database management products — be focused on price/performance, without little or no positive differentiation in the way of features.

My current customer list among the analytic DBMS specialists

(This is an updated version of an August, 2008 post.)

One of my favorite pages on the Monash Research website is the list of many current and a few notable past customers. (Another favorite page is the one for testimonials.) For a variety of reasons, I won’t undertake to be more precise about my current customer list than that. But I don’t think it would hurt anything to list the analytic/data warehouse DBMS/appliance specialists in the group. They are:

• Aster Data
• Greenplum
• Infobright
• Kickfire
• Kognitio
• Microsoft
• Netezza (my biggest client this year, probably, because of all the Enzee Universe appearances)
• Sybase
• Teradata
• Vertica
• Attivio, which may or may not be construed as being in the analytic DBMS business
• Clearpace, ditto

All of those are Monash Advantage members.

If you care about all this, you may also be interested in the rest of my standards and disclosures.

Netezza Q1 earning call transcript

I finally read the Netezza Q1 earnings call transcript, put out by Seeking Alpha.  Highlights included:

• Netezza got 14 new-name accounts and 21 follow-on deals. Average sale in both groups was right around $1 million.
• The economy is tough, deals are slipping, and nobody knows for sure what will happen.
• Netezza’s main head-to-head competitors are Oracle and Teradata.  Netezza claims good but not perfect win rates against each, but concedes that those vendors (especially Oracle) of course get other deals Netezza never sees.
• Netezza characterizes Teradata as offering its multiple product lines, trying to upsell many customers from cheaper to more expensive product lines, and being selectively aggressive about pricing. None of this is surprising to me.
• 80% of Netezza’s Q1 revenue, and perhaps even a higher fraction of new-name accounts, was in four vertical markets: “Digital media,” telecom, government, and financial services.
• Some time over the next few months, Netezza will give at least some more clarity about future products.

One tip for the Netezza folks, by the way, from this former stock analyst — you should never use the word “certainly” about a deal you haven’t closed yet. “Almost surely” could be OK, but “certainly” — well, it certainly was not the thing to say.

MapReduce user eHarmony chose Netezza over Aster or Greenplum

Depending on which IDG reporter you believe, eHarmony has either 4 TB of data or more than 12 TB, stored in Oracle but now analyzed on Netezza.  Interestingly, eHarmony is a Hadoop/MapReduce shop, but chose Netezza over Aster Data or Greenplum even so.  Price was apparently an important aspect of the purchase decision. Netezza also seems to have had a very smooth POC. Read more

The Netezza guys propose a POC checklist

The Netezza guys at “Data Liberators” are being a bit too cute in talking about FULL DISCLOSURE yet not actually saying they’re from Netezza — but only a bit, in that their identity is pretty clear even so.  That said, they’ve proposed a not-terrible checklist of how to conduct POCs.  Of course, vendor-provided as it is, it’s incomplete; e.g., there’s no real mention of a baseball-bat test.

Here’s the first part of the Netezza list, with my comments interspersed. Read more

Draft slides on how to select an analytic DBMS

I need to finalize an already-too-long slide deck on how to select an analytic DBMS by late Thursday night.  Anybody see something I’m overlooking, or just plain got wrong?

Edit: The slides have now been finalized.

Netezza’s marketing goes retro again

Netezza loves retro images in its marketing, such as classic rock lyrics, or psychedelic paint jobs on its SPUs.  (Given the age demographics at, say, a Teradata or Netezza user conference, this isn’t as nutty as it first sounds.) Netezza’s latest is a creative peoples-liberation/revolution riff, under the name Data Liberators.  The ambience of that site and especially its first download should seem instinctively familiar to anybody who recalls the Symbionese Liberation Army when it was active, or who has ever participated in a chant of “The People, United, Will Never Be Defeated!”

The substance of the first “pamphlet”, so far as I can make out, is that you should only trust vendors who do short, onsite POCs, and Oracle may not do those for Exadata. Read more

Gartner’s 2008 data warehouse database management system Magic Quadrant is out

Gartner’s annual Magic Quadrant for data warehouse DBMS is out.  Thankfully, vendors don’t seem to be taking it as seriously as usual, so I didn’t immediately hear about.  (I finally noticed it in a Greenplum pay-per-click ad.)  Links to Gartner MQs tend to come and go, but as of now here are two working links to the 2008 Gartner Data Warehouse Database Management System MQ.  My posts on the 2007 and 2006 MQs have also been updated with working links. Read more

High-performance analytics

For the past few months, I’ve collected a lot of data points to the effect that high-performance analytics – i.e., beyond straightforward query — is becoming increasingly important. And I’ve written about some of them at length. For example:

• MapReduce – controversial or in some cases even disappointing though it may be – has a lot of use cases.
• It’s early days, but Netezza and Teradata (and others) are beefing up their geospatial analytic capabilities.
• Memory-centric analytics is in the spotlight.

Ack. I can’t decide whether “analytics” should be a singular or plural noun. Thoughts?

Another area that’s come up which I haven‘t blogged about so much is data mining in the database. Data mining accounts for a large part of data warehouse use. The traditional way to do data mining is to extract data from the database and dump it into SAS. But there are problems with this scenario, including:

Read more

Big scientific databases need to be stored somehow

A year ago, Mike Stonebraker observed that conventional DBMS don’t necessarily do a great job on scientific data, and further pointed out that different kinds of science might call for different data access methods. Even so, some of the largest databases around are scientific ones, and they have to be managed somehow. For example:

• Microsoft just put out an overwrought press release. The substance seems to be that Pan-STARRS — a Jim Gray legacy also discussed in an August, 2008 Computerworld article — is adding 1.4 terabytes of image data per night, and one not so new database adds 15 terabytes per year of some kind of computer simulation output used to analyze protein folding. Both run on SQL Server, of course.
• Kognitio has an astronomical database too, at Cambridge University, adding 1/2 a terabyte of data per night.
• Oracle is used for a McGill University proteonomics database called CellMapBase. A figure of 50 terabytes of “mass storage” is included, which doesn’t include tape backup and so on.
• The Large Hadron Collider, once it actually starts functioning, is projected to generate 15 petabytes of data annually, which will be initially stored on tape and then distributed to various computing centers around the world.
• Netezza is proud of its ability to serve images and the like quickly, although off the top of my head I’m not thinking of a major customer it has in that area. (But then, if you just sell software, your academic discount can approach 100%; but if like Netezza you have an actual cost of goods sold, that’s not as appealing an option.)

Long-term, I imagine that the most suitable DBMS for these purposes will be MPP systems with strong datatype extensibility — e.g., DB2, PostgreSQL-based Greenplum, PostgreSQL-based Aster nCluster, or maybe Oracle.

How to tell Teradata’s product lines apart

Once Netezza hit the market, Teradata had a classic “disruptive” price problem – it offered a high end product, at a high price, sporting lots of features that not all customers needed or were willing to pay for. Teradata has at times slashed prices in competitive situations, but there are obvious risks to that, especially when a customer already has a number of other Teradata systems for which it paid closer to full price.

This year, Teradata has introduced a range of products that flesh out its competitive lineup. There now are three mainstream Teradata offerings, plus two with more specialized applicability. Teradata no longer has to sell Cadillacs to customers on Corolla budgets.

But how do we tell the five Teradata product lines apart? The names are confusing, both in their hardware-vendor product numbers and their data-warehousing-dogma product names, especially since in real life Teradata products’ capabilities overlap. Indeed, Teradata executives freely admit that the Teradata Data Mart Appliance 551 can run smaller data warehouses, while the Teradata Data Warehouse Appliance 2550 is positioned in large part at what Teradata quite reasonably calls data marts.

When one looks past the difficulties of naming, Teradata’s product lineup begins to make more sense. Let’s start by considering the three main Teradata products.

Read more

Eric Lai on Oracle Exadata, and some addenda

Eric Lai offers a detailed FAQ on Oracle Exadata, including a good selection of links and quotes. I’d like to offer a few comments in response: Read more

Netezza and Teradata on analytic geospatial data management

Geospatial data management is one of the flavors of the month:

• Last week, Teradata claimed it has the most sophisticated analytic geospatial data management capability.
• Also last week, Netezza’s newly acquired Netezza Spatial technology attracted a lot of attention.
• This week, Oracle called attention to its geospatial capabilities.

So I asked Netezza and Teradata what this geospatial analytics stuff is all about.

Read more

So what does Oracle Exadata mean for HP Neoview?

That HP is committed to selling a lot of data warehouse hardware — and probably data warehouse appliances in particular — seems obvious, for reasons including:

• HP bought a big BI/data warehousing consulting operation in Knightsbridge.
• HP has put considerable effort into its data warehouse appliance Neoview.
• HP CEO Mark Hurd comes from data warehouse appliance vendor Teradata.
• Data warehousing where the big bucks are.

But Oracle Exadata could produce those appliance sales. So where does HP Neoview fit in?

I was told by an investor today that HP’s investor relations department is saying Oracle Exadata is a Netezza competitor, while Neoview is more in the Teradata market. That’s laughable. Read more

Peter Batty on Netezza Spatial

As previously noted, I’m not up to speed on Netezza Spatial. Phil Francisco of Netezza has promised we’ll fix that ASAP. In the mean time, I found a blog by a guy named Peter Batty, who evidently:

• Knows a lot about geospatial data and its uses
• Is consulting to Netezza
• Is smart

Batty offers a lot of detail in two recent posts, intermixed with some gollygeewhiz about Netezza in general. If you’re interested in this stuff, Batty’s blog is well worth checking out. Read more

Web analytics — clickstream and network event data

It should surprise nobody that web analytics – and specifically clickstream data — is one of the biggest areas for high-end data warehousing. For example:

• I believe that both of the previously mentioned petabyte+ databases on Greenplum will feature clickstream data.
• Aster Data’s largest disclosed database, by almost two orders of magnitude, is at MySpace.
• Clickstream analytics is a big application area for Vertica Systems.
• Clickstream analytics is a big application area for Netezza.
• Infobright’s customer success stories appear to be concentrated in clickstream analytics.
• Coral8 tells me that CEP is also being used for clickstream data, although I suspect that a lot of Coral8’s evidence in that regard comes from a single flagship account. Edit: Actually, Coral8 has a bunch of clickstream customers.

Read more

Netezza overseas

22% of Netezza’s revenue comes from outside the US, at least if we use last quarter’s figures as a guide.  At first blush, that doesn’t sound like much.  Indeed, percentage-wise it surely lags behind Teradata, Greenplum (which has sold a lot in Asia/Pacific under Netezza’s former head of that region), and a few smaller competitors headquartered outside the US.  But a few conversations I had today suggest a rosier view.  Read more

Netezza application areas

I’m at the Netezza “Enzee” user conference in Orlando.  So one or more Netezza posts are in order.

One theme of the brief analyst meeting was Netezza’s increasing business focus on vertical markets.  In particular, Netezza is hiring managers for a range of vertical markets.  The commercial ones cited (at various levels of maturity) included: Read more

More mysteries regarding Oracle CDR load speed

Last spring, DATAllegro user John Devolites of TEOCO told me of troubles his firm had had loading CDRs (Call Detail Records) into Oracle, and how those had been instrumental in his eventual adoption of DATAllegro.  That claim was contemptously challenged in a couple of comment threads.

Well, tonight at the Netezza user conference, Netezza gave awards to its first customers.  The very first to accept was Jim Hayden, who’d bought Netezza for a company called Vibrant Solutions, which coincidentally was later acquired by TEOCO itself.  In front of hundreds of people, he talked about how, back in 2003, it had taken 23 hours to load 400 million CDRs into Oracle on Nextel’s behalf, but only 40 minutes on Netezza.

And I’ll erase the rest of what I’d drafted here, as it was dripping in sarcasm …

Teradata decides to compete head-on as a data warehouse appliance vendor

In a press release today that is surely timed to impinge on the Netezza user conference news cycle, Teradata has come out swinging. Highlights include:

• Teradata, which long avoided the “appliance” term, now says it sells both “data warehouse appliances” and “data mart appliances.” Indeed, it claims to have “invented the original appliance” — which is pretty close to being true.*
• Teradata claims its “new appliance easily delivers up to 5 to 10 times performance improvement over competitors’ appliances,” at $119,000 per terabyte US list price.
• Teradata claims a 150% faster “scan rate” than competitors. Teradata is surely thinking of Netezza when saying that.
• Teradata claims 10X performance improvement on “selected queries” vs. the “competition.”
• Teradata thinks its geospatial data management capability is better than competitors’, and that this is an important indicator of Teradata’s general overall greater sophistication.

Read more

Some Netezza customer metrics

From the conference call based on Netezza’s July, 2008 Q1, as of the end of Q1:

• There are now 191 Netezza customers.
• 18 of those were new.
• 78% of Netezza’s business was in North America and 22% was international.
• Netezza operates in 10 countries.
• “The top 4 vertical markets represented approximately 75% of our business, with those markets being telcos, retail, financial services, and the analytic service provider segment. “
• One analytic service provider was greater than 10% of revenue for the quarter, and is expected to keep buying a lot in subsequent quarters. Also, one analytic service provider standardized on Netezza. I’m guessing that’s the same customer.
• “We ended the quarter with 45 [quota] carrying teams made up of a sales rep and a systems engineer and our plan is to continue to hire direct sales teams at the pace of 3 to 5 per quarter every quarter. These direct reps accounted for 85% of the business while the indirect activity was 15% this quarter.”

Teradata/Netezza/Tesco kerfuffle

Netezza evidently put out a press release bragging of a competitive replacement of Teradata at UK retailing giant Tesco. That press release cannot be now found on Netezza’s site, but it lives on elsewhere. Meanwhile, Teradata has put out a press release in which Tesco is quoted emphatically contradicting what it is quoted as saying in the Netezza press release. While I haven’t discussed this with Netezza, my guess is that somebody there got a little overenthusiastic in advance of their user conference next week and thought they’d gotten a permission they really hadn’t.

Beyond that, I’d note that the Netezza quote made reference to around 25 heavy analytical users, while the Teradata quote talked of 8000 people across more than 2000 suppliers.

Read more

The layered messaging marketing model as applied to Netezza

I just put up a post claiming that enterprise IT marketing arguments commonly boil down to one of two layered messaging templates. Let’s test how that claim applies to one of the most innovative technology companies of this decade: Netezza.

Read more

More data on data warehouse sizes and issues

I spoke today with Paul Barth and Randy Bean of consultancy NewVantage Partners. The core of NewVantage’s business seems to be helping large enterprises (especially financial services) with their data warehouse strategies. Takeaways — none of which should shock regular readers of DBMS2 — included:

• Administrative cost and difficulty are often the single biggest issue in selecting analytic DBMS products.
• Oracle hits a wall around 10 terabytes of user data. The one customer NewVantage can think of with an Oracle data warehouse over 10 terabytes is fleeing Oracle for Netezza.
• NewVantage says that very specialized data warehouses on Oracle could conceivably be larger than that.
• NewVantage does have a customer on DB2/UDB in the 30-40 terabyte range. That customer does a lot of careful tuning to make it work.
• About 15% of NewVantage’s customers use Netezza. Few if any use newer analytic DBMS (but I got the sense more will soon). The rest rely on “traditional” DBMS, a group that includes Teradata.

Enterprises are buying multiple brands of analytic DBMS each

Over the past few weeks I’ve had a lot of NDA discussions about analytic DBMS vendors’ specific customers. And so I’ve been acutely aware of something I already sort of knew — just as there was in prior generations of database management technology, there’s huge overlap among analytic DBMS vendors’ customer bases as well. As they always have, enterprises are investing in multiple different brands of DBMS, even in cases where those DBMS can do pretty much the same things.

For example:

• Many Teradata users are buying newer technology too. But they aren’t actually throwing out Teradata.
• The same sometimes applies to Netezza already. At least two Netezza references are also references for a rival vendor.
• One outfit is among the biggest customers for two different analytic DBMS vendors, neither of which is Teradata or Netezza.
• One corporation is using or deploying four different brands of analytic DBMS.
• TEOCO is a big user of both DATAllegro and Netezza.

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