April 25th, 2008 Curt Monash
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:
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Small numbers of bulk updates, not large numbers of single-row updates.
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Queries that may involve examining or returning lots of data, rather than finding single records on a pinpoint basis.
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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 the rest of this entry »
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April 21st, 2008 Curt Monash
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 …
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April 21st, 2008 Curt Monash
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.
Posted in Data warehouse appliances, Data warehousing, Netezza, Teradata | 6 Comments »
April 21st, 2008 Curt Monash
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:
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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.
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$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.
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Scalability up to 24 nodes (>140 TB).
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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.
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What will be controversial performance, until customer-benchmark trends clearly emerge.
The Teradata 2500 is coming out of the chute with two customers – a new-customer retailer buying a single cabinet (i.e., 6.12 TB), and an existing customer for whom fewer details seem available. So far as I can tell, the sales force has had the product since late January, although the first leaks I got incorrectly suggested the system would only scale to a limited number of nodes.
Other products in the announcement included:
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The Teradata 5550, a routine annual upgrade to the Teradata 5500.
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The Teradata 550. This is a low-end, single-server SMP box introduced 9 or so months ago, originally meant for application development and testing. But some customers have been using it for deployment, and Teradata is now officially acknowledging that. It only scales to 2-3 TB of user data.
The Teradata 2500’s performance should be below the Teradata 5550’s for three reasons:
The same considerations apply to a comparison between the Teradata 2500 and the older Teradata 5000, but in that case they’re offset by a year of Moore’s Law benefit.
Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Database compression, Relational database management systems, Teradata | 1 Comment »
April 18th, 2008 Curt Monash
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:
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Kickfire’s technology has two main parts: A SQL co-processor chip and a MySQL storage engine.
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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.
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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.
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I don’t know whether the Kickfire chip is true custom silicon or an FPGA emulation.
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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.
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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).
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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.
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Like other MySQL storage engines, Kickfire inherits whatever data connectivity, stored procedure capabilities, user-defined functions ability, etc. that MySQL has.
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Kickfire has no paying customers, but does have a slide showing many logos of “prospects and beta customers.”
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Kickfire has no MPP capabilities at this time, but says adding those is “on the roadmap” and will be “easy.”
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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.
Posted in Analytics and analytic technologies, Columnar architectures, Data warehouse appliances, Data warehousing, Database compression, Database theory and practice, Kickfire, Open source RDBMS, Relational database management systems | 3 Comments »
April 8th, 2008 Curt Monash
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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Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Kickfire, MySQL, Relational database management systems | 7 Comments »
April 5th, 2008 Curt Monash
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:
Read the rest of this entry »
Posted in Analytics and analytic technologies, DATAllegro, Data warehouse appliances, Data warehousing, Dataupia, Greenplum, HP and Neoview, IBM and DB2, Infobright and Brighthouse, Kognitio and WX2, Microsoft and SQL*Server, Netezza, Oracle, ParAccel, Relational database management systems, Sybase, Teradata | 4 Comments »
April 5th, 2008 Curt Monash
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 the rest of this entry »
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April 1st, 2008 Curt Monash
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.
Posted in Data warehouse appliances, Data warehousing, Netezza | 2 Comments »
March 28th, 2008 Curt Monash
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 the rest of this entry »
Posted in Data warehouse appliances, Open source RDBMS, Relational database management systems | 1 Comment »
March 14th, 2008 Curt Monash
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 the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Microsoft and SQL*Server, Oracle, Relational database management systems | 16 Comments »
March 14th, 2008 Curt Monash
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 the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Dataupia, Portability, transparency, and plug-compatibility | No Comments »
February 26th, 2008 Curt Monash
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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Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Relational database management systems, Specific users, Teradata, eBay | No Comments »
February 15th, 2008 Curt Monash
This is the third of a five-part series on database management system choices. For the first post in the series, please click here.
High-end OLTP relational database management system vendors try to offer one-stop shopping for almost all data management needs. But as I noted in my prior post, their product category is facing two major competitive threats. One comes from specialty data warehouse database management system products. I’ve covered those extensively in this blog, with key takeaways including:
- Specialty data warehouse products offer huge cost advantages versus less targeted DBMS. This applies to purchase/maintenance and administrative costs alike. And it’s true even when the general-purposed DBMS boast data warehousing features such as star indexes, bitmap indexes, or sophisticated optimizers.
- The larger the database, the bigger the difference. It’s almost inconceivable to use Oracle for a 100+ terabyte data warehouse. But if you only have 5 terabytes, Oracle is a perfectly viable – albeit annoying and costly – alternative.
- Most specialty data warehouse products have a shared-nothing architecture. Smaller parts are cheaper per unit of capacity. Hence shared nothing/grid architectures are inherently cheaper, at least in theory. In data warehousing, that theoretical possibility has long been made practical.
- Specialty data warehouse products with row-based architectures are commonly sold in appliance formats. In particular, this is true of Teradata, Netezza, DATAllegro, and Greenplum. One reason is that they’re optimized to stream data off of disk fairly sequentially, as opposed to relying on random seeks.
- Specialty data warehouse products with columnar architectures are commonly available in software-only formats. Even so, Vertica and ParAccel also boast appliance deals, with HP and Sun respectively.
- There is tremendous technical diversity and differentiation in the specialty data warehouse system market.
Let me expand on that last point. Different features may or may not be important to you, depending on whether your precise application needs include:
Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Database diversity, Database theory and practice, Relational database management systems | 17 Comments »
January 26th, 2008 Curt Monash
I had a call today with Kognitio execs Paul Groom and John Thompson. Hopefully I can now clear up some confusion that was created in this comment thread. (Most of what I wrote about Kognitio in October, 2006 still applies.) Here are some highlights. Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Kognitio and WX2, Relational database management systems | 9 Comments »
January 23rd, 2008 Curt Monash
Edit: This post is superseded by our analysis of the new Teradata 2500 data warehouse appliance.
One of Teradata’s competitors believes they got an accurate leak about a new low-end Teradata appliance. Teradata is neither confirming nor denying. I believe the leak.
I’m not going to give product or pricing details, which in any case could be subject to change before a final product release. But the general idea is:
- Commodity Dell servers.
- Some of the higher-end software stripped out.
- Limit on the number of nodes, leading to a database size limit somewhere in the tens of terabytes.
It will be interesting to see whether Teradata can come out with something that’s closely competitive in price, performance, and administrative ease to what the newer data warehouse appliance vendors offer, yet upgrades cleanly to full-sophistication Teradata systems for those who choose to pursue that path.
Posted in Data warehouse appliances, Data warehousing, Relational database management systems, Teradata | No Comments »
January 14th, 2008 Curt Monash
EMC is rolling out solid-state drives later this quarter. The press release mentions the word “terabyte”, so this is for non-trivial systems. And by the way, 100,000 write/erase cycles before something wears out is several per hour, so that’s a non-problem for data warehousing.
ParAccel and SAP already offer RAM-based appliances. I suspect we’ll see appliances based on solid-state drives before long. I also wouldn’t be shocked if a non-appliance vendor such as Oracle suddenly jumped into this area, trying to use it as a way to leapfrog the appliance vendors.
Posted in Data warehouse appliances, Data warehousing | 1 Comment »
January 10th, 2008 Curt Monash
Netezza is promising petabyte-scale appliances later this year, up from 100 terabytes. That’s user data (I checked), and assumes 2-3X compression, or a little less than they think is actually likely. I.e., they’re describing their capacity in the same kinds of terms other responsible vendors do. They haven’t actually built and tested any 1 petabyte systems internally yet, but they’ve gone over 100 terabytes.
Basically, this leaves Netezza’s high-end capability about 10X below Teradata’s. On the other hand, it should leave them capable of handling pretty much every Teradata database in existence. Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Netezza, Teradata | No Comments »
December 14th, 2007 Curt Monash
There are at least 16 different vendors offering appliances and/or software that do database management primarily for analytic purposes.* That’s a lot to keep up with,. So I’ve thrown together a little overview of the analytic data management landscape, liberally salted with links to information about specific vendors, products, or technical issues. In some ways, this is a companion piece to my prior post about data warehouse appliance myths and realities.
*And that’s just the tabular/alphanumeric guys. Add in text search and you run the total a lot higher.
Numerous data warehouse specialists offer traditional row-based relational DBMS architectures, but optimize them for analytic workloads. These include Teradata, Netezza, DATAllegro, Greenplum, Dataupia, and SAS. All of those except SAS are wholly or primarily vendors of MPP/shared-nothing data warehouse appliances. EDIT: See the comment thread for a correction re Kognitio.
Numerous data warehouse specialists offer column-based relational DBMS architectures. These include Sybase (with the Sybase IQ product, originally from Expressway), Vertica, ParAccel, Infobright, Kognitio (formerly White Cross), and Sand. Read the rest of this entry »
Posted in Analytics and analytic technologies, Cognos and Applix TM1, DATAllegro, Data warehouse appliances, Data warehousing, Dataupia, Greenplum, IBM and DB2, Kognitio and WX2, Netezza, Oracle, ParAccel, Relational database management systems, SAS Institute, Sybase, Teradata, Vertica Systems | 10 Comments »
December 7th, 2007 Curt Monash
The proximate cause for today’s flurry of Netezza-related posts is that the company has finally rolled out its compression story. In a nutshell, Netezza has developed its own version of columnar delta compression, slated to ship May, 2008. It compresses 2-5X, with the factor sometimes going up into double digits. Netezza estimates this produces a 2-3X improvement in overall performance, with the core marketing claim being that performance will “double” from compression alone. Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Database compression, Database theory and practice, Netezza, Relational database management systems | No Comments »
December 7th, 2007 Curt Monash
In 1993, Ted Codd introduced the term OLAP (OnLine Analytic Processing) to describe data management that wasn’t optimized for OLTP (OnLine Transaction Processing). Later in the 1990s, Henry Morris of IDC introduced the term analytic applications to describe apps that weren’t transactional. Since then, no better word than “analytic” has emerged to cover the broad class of IT apps and technologies that aren’t focused on transactional processing.
In the latest incarnation, analytic appliances are coming to the fore. Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Netezza, Relational database management systems, Vertica Systems | No Comments »
December 7th, 2007 Curt Monash
I’ve bashed Netezza repeatedly for secrecy and obscurity about its technology and technical plans. Well, they’re getting a lot better. The latest post in a Netezza company blog, by marketing exec Phil Francisco, lays out their story clearly and concisely. And it’s backed up by a white paper that does more of the same. In particular, Page 11 of that white paper spells out possible future directions for enhancement, such as better compression, encryption, join filtering, and Netezza Developer Network stuff. Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Netezza, Relational database management systems | 2 Comments »
December 7th, 2007 Curt Monash
I talked with Netezza today, and finally understand better why they don’t have node-to-node data shipping problems with only 1-gigabit (gigE) interconnects:
- Netezza boxes have lots of relatively small nodes, so all else being equal, each individual node has less communicating to do than, say, a DATAllegro node does.
- It’s not just just 1-gigabit. There’s a hierarchical communications architecture, and at one level in the hierarchy switches are talking to each other through 32 parallel 1-gigabit channels at a time.
Posted in Data warehouse appliances, Netezza | No Comments »
December 3rd, 2007 Curt Monash
Borrowing the “Fact or fiction?” meme from the sports world:
- Data warehouse appliances have to have specialized hardware. Fiction. Indeed, most contenders except Teradata and Netezza — for example, DATAllegro, Vertica, ParAccel, Greenplum, and Infobright — offer Type 2 appliances. (Dataupia is another exception.)
- Specialized hardware is a dead-end for data warehouse appliances. Fiction. If it were easy for Teradata to replace its specialized switch technology, it would have done so a decade ago. And Netezza’s strategy has a lot of appeal.
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Data warehouse appliances are nothing new, and failed long ago. Fiction, but only because of Teradata. 1980s appliance pioneer Britton-Lee didn’t do so well (it was actually bought by Teradata). IBM and ICL (Britain’s national-champion hardware company) had content-addressable data store technology that went nowhere.
- Since data warehouse appliances failed long ago, they’ll fail now too. Fiction. Shared-nothing MPP is a fundamental advantage of appliances. So are various index-light strategies. Data warehouse appliances are here to stay.
- Data warehouse appliances only make sense if your main database management system can’t handle the job. Fiction. There are dozens of data warehouse appliances managing under 5 terabytes of user data, if not under 1 terabyte. True, some of them are legacy installations, dating back to when Oracle couldn’t handle that much data well itself. But new ones are still going in. Even if Oracle or Microsoft SQL Server can do the job, a data warehouse appliance is often a far superior — cheaper, easier to deploy and keep running, and/or better performing — alternative.
- Data warehouse appliances are just for data marts. For your full enterprise data warehouse, use a conventional DBMS. Part fact, part fiction. It depends on the appliance, and on the complexity of your needs. Teradata systems can do pretty much everything. Netezza and DATAllegro, two of the oldest data warehouse appliance startups, have worked hard on their concurrency issues and now can support fairly large user or reporting loads. They also can handle reasonable volumes of transactional or trickle-feed updates, and probably can support full EDW requirements for decent-sized organizations. Even so, there are some warehouse use cases for which they’re ill-suited. Newer appliance vendors are more limited yet.
- Analytic appliances are just renamed data warehouse appliances. Fact, even if misleading. Netezza is using the term “analytic appliance” to highlight additional things one can do on its boxes beyond answering queries. But those are still operations on a data mart or data warehouse. And Vertica is using the term “analytic appliance” to mean exactly what “data warehouse” means.
- Teradata is the leading data warehouse appliance vendor. More fact than fiction. Some observers say that Teradata systems aren’t data warehouse appliances. But I think they are. Competitors may be superior to Teradata in one or the other characteristic trait of appliances – e.g., speed of installation – but it’s hard to define “appliances” in an objective way that excludes Teradata.
If you liked this post, you might also like one on text mining fact and fiction.
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Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Relational database management systems | 3 Comments »
November 29th, 2007 Curt Monash
Netezza reported a big October quarter, ahead of expectations. And official guidance for next quarter is essentially flat quarter-over-quarter, suggesting Q3 was indeed surprisingly big. However, Netezza’s year-over-year growth for Q3 was a little under 50%, suggesting the quarter wasn’t so remarkable after all. (Netezza has a January fiscal year.)
Tentative conclusion: Netezza just tends to have big October quarters, perhaps by timing sales cycles to finish soon after the late September user conference. If Netezza’s user conference ever moves to later in the fall, expect Q3 to be weak that year.
Netezza reported 18 new customers, double last year’s figure. Read the rest of this entry »
Posted in Analytics and analytic technologies, Data warehouse appliances, Data warehousing, Greenplum, Kognitio and WX2, Netezza, Relational database management systems | 3 Comments »