Three happy 100 terabyte-plus customers for DATAllegro

Over on my Network World blog, I asked the question “So who are DATAllegro’s actual current customers?” As regular readers know, that’s a fairly hard question to answer. TEOCO is widely known as DATAllegro’s flagship reference, but after that the list gets thin in a hurry.

As a by-the-by to other discussions, DATAllegro Stuart Frost undertook to respond in part himself. Specifically, he gave me two names of two other happy customers that are or imminently will be running DATAllegro against 100+ terabytes of user data. Read more

Netezza update

In my usual dual role, I called Phil Francisco of Netezza to lay some post-Microsoft/DATAllegro consulting on him late on a Friday night — and then took the opportunity of being on the phone with him to get a general Netezza update. Netezza’s July quarter just ended, so they’re still in quiet period, so I didn’t press him for a lot of numerical detail. More generally, I didn’t find a lot out that wasn’t already covered in my May Netezza update. But notwithstanding all those disclaimers, it was still a pretty interesting chat.

My strongest takeaway was that Netezza sees concurrency as a significant competitive advantage. This is reflected in POCs, where Netezza guides prospects to simulate real-life mixed workloads. It also reflects the Netezza customer base. Phil says Netezza has “busy” warehouses with up to 80 terabytes of user data, with lots of busy ones in the single-digit to 20ish terabyte range. Multiple Netezza references have 100s of concurrent users, and the 1000 mark has been crossed.

Speaking of concurrency, Phil had a clear opinion of the typical Sybase IQ installation — a small reporting mart, supporting hundreds or thousands of users, but probably not a lot of ad hoc query. On the other hand, he recalls outright competing against Sybase only twice in the past year.

The vendor Netezza does see the most is, no surprise, Oracle. He put Oracle at 60ish percent, with most of the rest divided among Teradata and DB2 (only a few Microsoft SQL Server). Among the other new data warehouse specialists, Greenplum comes up the most often. (There was some confusion between “competitor” and “incumbent” in our discussion, and the sample sizes are small anyway, so fine levels of detail shouldn’t be taken too seriously.)

On the advanced analytics side, it sounds as if SAS integration akin to Teradata’s will happen sooner than any significant integration of Netezza’s own NuTech acquisition.

How will Oracle save its data warehouse business?

By acquiring DATAllegro, Microsoft has seriously leapfrogged Oracle in data warehouse technology. All doubts about maturity and versatility notwithstanding, DATAllegro has a 10X or better size advantage (actually, I think it’s more like 20-40X) versus Oracle in warehouses its technology can straightforwardly handle. Oracle cannot afford to let this move go unanswered.

It’s of course possible that Oracle has been successfully developing comparable data warehouse technology internally. But it’s unlikely. Oracle hasn’t done anything that radical, internally and successfully, for about 15 years, RAC (Real Application Clusters) excepted. (I.e., since the object/relational extensibility framework started in Release 7.) So in all likelihood, the answer will come via acquisition. I think there are four candidates that make the most sense: Teradata, Vertica, ParAccel, and Greenplum. Kognitio (controlled by former Oracle honcho Geoff Squire) might be in the mix as well. Netezza is probably a non-starter because of its hardware-centric strategy.

Here’s why I’m emphasizing Teradata, Vertica, ParAccel, and Greenplum:

Read more

Microsoft is buying DATAllegro

I’ve long argued that:

• Oracle and Microsoft are doomed in the data warehouse market unless they acquire MPP/shared-nothing data warehouse DBMS and/or data warehouse appliances.
• DATAllegro is the ideal acquisition for either of them.

Microsoft has now validated my claim by agreeing to buy DATAllegro. As you probably know, we’ve been covering DATAllegro extensively, as per the links listed below.

Basic deal highlights include:

Read more

Declaration of Data Independence (humor)

The data warehouse appliance industry has a well-developed funny bone. Dataupia’s contribution is a Declaration of Data Independence, which begins:

When in the Course of an increasingly competitive global economy it becomes necessary for one data set to dissolve its connections to a constraining environment, the separate but inherently unequal station to which the Laws of Whose budget is larger prevails.

Related links:

• Cartoons from DATAllegro
• April Fool press release from Netezza

Oracle Optimized Warehouse Initiative

Oracle’s response to data warehouse appliances — and to IBM’s BCUs (Balanced Configuration Units) — so far is the Oracle Optimized Warehouse Initiative (OOW, not to be confused with Oracle Open World). A small amount of information about Oracle Optimized Warehouse can be found on Oracle’s website. Another small amount can be found in this recent long and breathless TDWI article, full of such brilliancies as attributing to the data warehouse appliance vendors the “claim that relational databases simply aren’t cut out for analytic workloads.” (Uh, what does he think they’re running — CODASYL DBMS?)

So far as I can tell, what Oracle Optimized Warehouse — much like IBM’s BCU — boils down to is the same old Oracle DBMS, but with recommended hardware configuration and tuning parameters. Thus, a lot of the hassle is taken out of ordering and installing an Oracle data warehouse, which is surely a good thing. But I doubt it does much to solve Oracle’s problems with price, price/performance, or the inevitable DBA hassles derived from a poorly-performing DBMS.

DATAllegro on compression

DATAllegro CEO Stuart Frost has been blogging quite a bit recently (and not before time!). A couple of his posts have touched on compression. In one he gave actual numbers for compression, namely:

DATAllegro compresses between 2:1 and 6:1 depending on the content of the rows, whereas column-oriented systems claim 4:1 to 10:1.

In another recent post, Stuart touched on architecture, saying:

Due to the way our compression code works, DATAllegro’s current products are optimized for performance under heavy concurrency. The end result is that we don’t use the full power of the platform when running one query at a time.

Read more

Data warehouse appliance power user TEOCO

If you had to name super-high-end users of data warehouse technology, your list might start with a few retailers, credit data processors, and telcos, plus the US intelligence establishment. Well, it turns out that TEOCO runs outsourced data warehouses for several of the top US telcos, making it one of the top data warehouse technology users around.

A few weeks ago, I had a fascinating chat with John Devolites of TEOCO. Highlights included:

• TEOCO runs a >200 TB DATAllegro warehouse for a major US telco. (When we hear about a big DATAllegro telco site that’s been in production for a while, that’s surely the one they’re talking about.)
• TEOCO runs around 450 TB total of DATAllegro databases across its various customers. (When Stuart Frost blogs of >400 TB “systems,” that may be what he’s talking about.)
• TEOCO likes DATAllegro better than Netezza, although the margin is now small. This is mainly for financial reasons, specifically price-per-terabyte. When TEOCO spends its own money without customer direction as to appliance brand, it buys DATAllegro.
• TEOCO runs at least one 50 TB Netezza system — originally due to an acquisition of a Netezza user — with more coming. There also is more DATAllegro coming.
• TEOCO feels 15-30 concurrent users is the current practical limit for both DATAllegro and Netezza. That’s greater than it used to be.
• Netezza is a little faster than DATAllegro on a few esoteric queries, but the difference is not important to TEOCO’s business.
• Official price lists notwithstanding, TEOCO sees prices as being in the $10K/TB range. DATAllegro’s price advantage has shrunk greatly, as others have come down to more or less match. However, since John stated his price preference for DATAllegro as being in the present tense, I presume the price match isn’t perfect.
• Teradata was never a serious consideration, for price reasons.
• In the original POC a few years ago, the incumbent Oracle — even after extensive engineering — couldn’t get an important query down under 8 hours of running time. DATAllegro and Netezza both handled it in 2-3 minutes. Similarly, Oracle couldn’t get the load time for 100 million call detail records (CDRs) below 24 hours.
• Applications sound pretty standard for telecom: Lots of CDR processing — 550 million/day on the big DATAllegro system cited above. Pricing and fraud checking. Some data staging for legal reasons (giving the NSA what it subpoenas and no more).

Netezza on compression

Phil Francisco put up a nice post on Netezza’s company blog about a month ago, explaining the Netezza compression story. Highlights include:

• Like other row-based vendors, Netezza compresses data on a column-by-column basis, then stores the results in rows. This is obviously something of a limitation — no run-length encoding for them — but can surely accommodate several major compression techniques.
• The Netezza “Compress Engine” compresses data on a block-by-block basis. This is a disadvantage for row-based systems vs. columnar ones in the area of compression, because columnar systems have more values per block to play with, and that yields higher degrees of compression. And among row-based systems, typical block size is an indicator of compression success. Thus, DATAllegro probably does a little better at compression than Netezza, and Netezza does a lot better at compression than Teradata.
• Netezza calls its compression “compilation.” The blog post doesn’t make the reason clear. And the one reason I can recall confuses me. Netezza once said the compression extends at least somewhat to columns with calculated values. But that seems odd, as Netezza only has a very limited capability for materialized views.
• Netezza pays the processing cost of compression in the FPGA, not the microprocessor. And so Netezza spins the overhead of the Compress Engine as being zero or free. That’s actually not ridiculous, since Netezza seems to have still-unused real estate on the FPGA for new features like compression.

Read more

Netezza has an EMC deal too

Netezza has an EMC deal too. As befits a hardware vendor, Netezza has an actual OEM relationship with EMC, in which it is offering CLARiiONs built straight into NPS appliances. 5 TB of CLARiiON will be free in any Netezza system from 2 racks on upward. (A rack holds about 12.5 TB.) In addition, you’ll be able to buy 10 TB more of CLARiiON in every Netezza rack, if you want. The whole thing is supposed to ship before year-end. Read more

Netezza, enterprise data warehouses, and the 100 terabyte mark

Phil Francisco of Netezza checked in tonight with some news that will be embargoed for a few hours. While I had him on the phone anyway, I asked him about large databases and/or enterprise data warehouses. Highlights included:

• Netezza has one customer with 200 TB of user data. The name is confidential (but he told me who it was).
• Netezza has sold 15 or so of its NPS 10-800s, which are rated at 100 TB capacity.
• The second-largest database in production on Netezza is probably 80 TB or so at Catalina Marketing, which has been a Netezza early adopter all along.
• Netezza’s biggest users typically have a handful (literally — off the top of his head, Phil said “4 to 6″) of applications, each with its own primary set of fact tables.
• Each application-specific set of fact tables in such big-honking-data-mart installations is usually either of cardinality one, or else a small set sharing a common hash key.
• Phil insists Netezza isn’t exaggerating when it claims to have true enterprise data warehouse installations. What he means by an EDW is something that is an enterprise’s primary data warehouse, is used by lots of departments, draws data from lots of sources, has loads going on at various points during the day, and has 100s if not 1000s of total users.
• Netezza’s biggest EDW has about 30 TB of user data. Phil wouldn’t tell me the name of that customer.

ParAccel unveils its EMC-related appliance strategy

Embargoes are getting ever more stupid these days, wasting analysts’ and bloggers’ time in doomed attempts to micromanage the news flow. ParAccel is no exception to the rule. An announcement that’s actually been public knowledge for a couple of months was finally made official a few minutes ago. It’s an appliance, or at least an attempt to gain customers for an appliance. The core ideas include:

• ParAccel’s usual shared-nothing configuration is hooked up to SAN-based EMC storage at the back end.
• Around half of the total data is on internal (i.e., node-specific) disks, mirrored on the storage device. The rest of the data lives only on the EMC device. Logically, all this data is integrated. So hopefully you’ll be able to process more data per unit of time than you could on a standard ParAccel configuration.
• Also, different parts of the EMC device are dedicated to different ParAccel nodes. So, while this isn’t a shared-nothing architecture, at least it’s shared-not-very-much. (DATAllegro does something similar, although without the mirroring on direct-attached storage.)
• Backup, snapshotting, and so on are inherited from EMC. Administration will increasingly be integrated with EMC’s.

Yet another data warehouse database and appliance overview

For a recent project, it seemed best to recapitulate my thoughts on the overall data warehouse specialty DBMS and appliance marketplace. While what resulted is highly redundant with what I’ve posted in this blog before, I’m sharing anyway, in case somebody finds this integrated presentation more useful. The original is excerpted to remove confidential parts.

… This is a crowded market, with a lot of subsegments, and blurry, shifting borders among the subsegments.

… Everybody starts out selling consumer marketing and telecom call-detail-record apps. …

Oracle and similar products are optimized for updates above everything else. That is, short rows of data are banged into tables. The main indexing scheme is the “b-tree,” which is optimized for finding specific rows of data as needed, and also for being updated quickly in lockstep with updates to the data itself.

By way of contrast, an analytic DBMS is optimized for some or all of:

• Small numbers of bulk updates, not large numbers of single-row updates.

• Queries that may involve examining or returning lots of data, rather than finding single records on a pinpoint basis.

• Doing arithmetic calculations – commonly simple arithmetic, sorts, etc. – on the data.

Database and/or DBMS design techniques that have been applied to analytic uses include:

Read more

DATAllegro finally has a blog

It took a lot of patient nagging, but DATAllegro finally has a blog. Based on the first post, I predict:

• DATAllegro’s blog will live up to CEO Stuart Frost’s talent for clear, interesting writing.
• Like a number of other vendor blogs — e.g., Netezza’s — DATAllegro’s will have infrequent but usually long posts.

The crunchiest part of the first post is probably

Another very important aspect of performance is ensuring sequential reads under a complex workload. Traditional databases do not do a good job in this area - even though some of the management tools might tell you that they are! What we typically see is that the combination of RAID arrays and intervening storage infrastructure conspires to break even large reads by the database into very small reads against each disk. The end result is that most large DW installations have very large arrays of expensive, high-speed disks behind them - and still suffer from poor performance.

I’ve pounded the table about sequential reads multiple times — including in a (DATAllegro-sponsored) white paper — but the point about misleading management tools is new to me.

Now if I could just get a production DATAllegro reference, I’d be completely happy …

Netezza pricing

In connection with the announcement of the Teradata 2500, I asked some Teradata competitors about pricing. Netezza’s response amounted to “We don’t disclose list pricing, but our cheapest system handles about 3 1/4 TB and sells for under $200K.” So Netezza’s actual pricing is well below the list price of the Teradata 2500.

Teradata introduces lower-cost appliances

After months of leaks, Teradata has unveiled its new lines of data warehouse appliances, raising the total number either from 1 to 3 (my view) or 0 to 2 (what you believe if you think Teradata wasn’t previously an appliance vendor). Most significant is the new Teradata 2500 series, meant to compete directly with the smaller data warehouse specialists. Highlights include:

• An oddly precise estimated capacity of “6.12 terabytes”/node (user data). This estimate is based on 30% compression, which is low by industry standards, and surely explains part of the price umbrella the Teradata 2500 is offering other vendors.

• $125K/TB of user data. Obviously, list pricing and actual pricing aren’t the same thing, and many vendors don’t even bother to disclose official price lists. But the Teradata 2500 seems more expensive than most smaller-vendor alternatives.

• Scalability up to 24 nodes (>140 TB).

• Full Teradata application-facing functionality. Some of Teradata’s rivals are still working on getting all of their certifications with tier-1 and tier-2 business intelligence tools. Teradata has a rich application ecosystem.

• What will be controversial performance, until customer-benchmark trends clearly emerge.

Read more

Kickfire kicks off

I chatted with Raj Cherabuddi and others on the Kickfire (formerly C2) team for over an hour on Monday, and now have a better sense of their story. There are some very basic questions I still don’t have answers to; I’ll fill those in when I can.

Highlights of what I have and haven’t figured out so far include:

• Kickfire’s technology has two main parts: A SQL co-processor chip and a MySQL storage engine.

• Kickfire makes a Type 0 appliance. If I understood correctly, it contains the chip, a couple of standard CPU cores, and 64 gigs of RAM. Or else it contains just the chip, and is meant to be hooked up to a 2U box with 64 gigs of RAM. I’m confused.

• The Kickfire box can handle up to 3 terabytes of user data. The disk required for that is 4-5 terabytes without redundancy, 2X with. Based on that formulation and other clues, I’m guessing Kickfire — unlike other appliance vendors — doesn’t build in storage itself.

• I don’t know whether the Kickfire chip is true custom silicon or an FPGA emulation.

• The essential idea of the chip is dataflow programming for SQL, with pipelining between operations. This eliminates the overhead of registers and context switching. I don’t know what the trade-offs are, if any.

• Kickfire’s database software is columnar, operating on compressed data even in RAM. In that, Kickfire’s story is most similar to Vertica’s, although I’m guessing Exasol may do something similar as well. Like Vertica, Kickfire uses multiple compression methods (they’re reluctant to give detail, but agreed it would be fair to say they use both something like dictionary/token and something like delta compression).

• Kickfire’s software is ACID-compliant. You can do incremental loads or trickle feeds. Bulk load speed is 100 Gb/hour. Kickfire’s solution for the traditional problem of updating column stores is called “snapshots.” Without giving details, they position that as similar to the Vertica solution.

• Like other MySQL storage engines, Kickfire inherits whatever data connectivity, stored procedure capabilities, user-defined functions ability, etc. that MySQL has.

• Kickfire has no paying customers, but does have a slide showing many logos of “prospects and beta customers.”

• Kickfire has no MPP capabilities at this time, but says adding those is “on the roadmap” and will be “easy.”

• Kickfire submitted a 100 Gb TPC-H result, in which it beat the previous leaders — Exasol, ParAccel, and Microsoft – on price-performance, and lagged only Exasol and ParAccel on absolute performance. Kickfire is extremely proud of this. Indeed, I don’t recall another vendor ascribing that much weight to them in the entire history of TPCs.* Kickfire seems unfazed by the fact that its result is for a system listed with a ship date 6 months in the future (I’m guessing that’s the latest the TPC will allow), while the other results are for systems available today.

*Somebody – perhaps adman extraordinaire Rick Bennett? — may want to check my memory on this, but I think Oracle’s famed “Gentlemen, start your snails” ad in the early 1990s was about PC World tests, not TPCs. Oracle also had an ad about WW1-style planes nosediving, but I don’t think those referenced TPCs either.

Kickfire is de-cloaking

Kickfire, the renamed C2, is doing one of those buzz-building rollouts in which they make sure the first word comes from people on their payroll golly-gee-whizzing. You can see those at Xarpb and Diamond Notes, as well as a forthcoming article in MySQL magazine. Farhan Mashraqi also appears to be involved. Kickfire is also sponsoring the MySQL user conference next week.

I plan to write more after I get some substance, but a few things seem clear:

1. Kickfire’s product is an appliance that functions as a MySQL storage engine.
2. There’s a custom chip involved.
3. Kickfire plans to throw around the “stream processing” buzzphrase a lot.

Now, “stream processing” means a lot of different things to different people. E.g., Netezza uses the phrase just because their FPGA throws away a lot of data before ever routing it to more conventional SQL processing. But pending a briefing, I’m guessing that Kickfire’s sense is similar to what underlies the case for using CEP in BI.

Edit: Here’s an update after an actual Kickfire briefing.

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Positioning the data warehouse appliances and specialty DBMS

There now are four hardware vendors that each offer or seem about to announce two different tiers of data warehouse appliances: Sun, HP, EMC, and Teradata. Specifically:

• Sun partners with both Greenplum and ParAccel.

• HP sells Neoview, and also is partnered with Vertica.

• EMC (together with Dell in North America and Bull in Europe) sells DATAllegro. Now EMC is also entering a partnership with ParAccel.

• Teradata is pretty far down the road toward releasing a low-end product.

Read more

EMC is partnering with ParAccel

A talk about a ParAccel/EMC partnership has been promised for a forthcoming EMC user conference. Otherwise, ParAccel is exposing no useful information on the matter.*

*So what else is new?

The talk is called Highly Scalable Analytic Appliance Powered by EMC and ParAccel, and the abstract says: Read more

Netezza’s April Fool press release

Short and cute. Even makes a genuine marketing point (low power consumption), and ties into past marketing gimmicks (they’ve played Pimp My SPU in the past, with dramatic paint jobs).

Netezza Corporation (NYSE Arca: NZ), the global leader in data warehouse and analytic appliances, today introduced a limited-edition range of its award-winning Netezza system. Expected to become an instant industry collectible, the systems can now be purchased in a variety of color finishes – pink, blue, red or silver. The standard gun-metal gray unit will continue to be the default option for orders requiring eight or more units, to ensure availability.

Affectionately known as ‘the Netezza’ by customers and partners, the systems not only offer unparalleled processing performance, but the secret sauce of its innovative design is also leading the way in effective power and cooling management – making it a truly green option for any data center.

Not earth-shaking — even if it purports to be earth-saving — but unless I’ve overlooked a biggie, there isn’t much competition this rather lame April Fool’s year.

Disruption versus chasm crossing in the database market

The 451 Group just released a report on open source DBMS adoption. In a blog post announcing same, Matthew Aslett wrote (emphasis mine):

you only have to look at the comparative revenues of the open source and proprietary vendors to see that there is a vast chasm to be crossed.

“Chasm” memes were introduced by Geoffrey Moore, founder of the Chasm Group and author of Crossing the Chasm. His defining example was Oracle, and the database market in general. The core insight was that platform markets get to tipping points, after which the leaders have tremendous advantages that make them tend to remain leaders for a good long time.

The sequel to “chasm” theory is Clayton Christensen’s “disruption” rubric, popularized in The Innovator’s Dilemma. I’ve argued previously that the DBMS market is being disrupted, in both the ways that Christensen records: Read more

Data warehousing with paper clips and duct tape

An interesting part of my conversation with Dataupia’s CTO John O’Brien came when we talked about data warehousing in general. On the one hand, he endorsed the view that using Oracle probably isn’t a good idea for data warehouses larger than 10 terabytes, with SQL Server’s limit being well below that. On the other hand, he said he’d helped build 50-60 terabyte warehouses in Oracle years ago.

The point is that to build warehouses that big in Oracle or other traditional DBMS, you have to pull out a large bag of tricks. Read more

Dataupia catch-up

I had a catch-up phone meeting with Dataupia, since I hadn’t spoke with the company since the middle of last year. Like several other companies in the data warehouse specialist market, Dataupia can be annoyingly secretive. On the plus side – and this is very refreshing — Dataupia doesn’t seem to expect credit for accomplishments beyond those they’re willing to provide actual evidence for.

What I’ve gleaned about Dataupia’s customer activity to date amounts to: Read more

The biggest eBay database

There’s been some confusion over my post about eBay’s multiple petabytes of data. So to clarify, let me say:

• eBay’s figure of >1.4 petabytes of data — for its largest single analytic database — counts disks or something, not raw user data.
• I previously published a strong conjecture that the database vendor in question was Teradata, which is definitely an eBay supplier. In particular, it is definitely not an Oracle data warehouse.
• While eBay isn’t saying who it is either — not even off-the-record — the 50%ish compression figures they experience just happen to map well to Teradata’s usual range.
• Edit: Just to be clear — not that there was any doubt, but I have reconfirmed that eBay is a Teradata user, in or including eBay’s Paypal division.

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