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.
| Categories: Data warehouse appliances, Data warehousing, Netezza, Pricing, Teradata | 11 Comments |
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.
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, Database compression, Pricing, Teradata | 6 Comments |
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:
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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.
Relational purists should root for ScaleDB
I just put up a long post about a small development-stage company, ScaleDB. The punchline is that ScaleDB has a data access method — an extension of Patricia tries — that gives referential integrity and updatable views for free.
People who think current “relational” DBMS aren’t relational enough often suggest that’s the kind of foundation DBMS should have. And unlike Required Technologies’ TransRelational (TM) shtick, ScaleDB’s really is an OLTP-oriented approach.
| Categories: MySQL, Theory and architecture, TransRelational | Leave a Comment |
ScaleDB presents The Revenge of the Pointer
The MySQL user conference is upon us, and hence so are MySQL-related product announcements, including storage engines. One such is Kickfire. ScaleDB — smaller and earlier-stage — is another.
In a nutshell, ScaleDB’s proposition is:
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Innovative approach to indexing relational DBMS, providing performance advantages.
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Shared-everything scale-up that ScaleDB believes will leapfrog the MySQL engine competition already in Release 1. (In my opinion, this is the least plausible part of the ScaleDB story.)
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State-of-the-art me-too facilities for locking, logging, replication/fail-over, etc., also already in Release 1.
Like many software companies with non-US roots, ScaleDB seems to have started with a single custom project, using a Patricia trie indexing system. Then they decided Patricia tries might be really useful for relational OLTP as well. The ScaleDB team now features four developers, plus half-time or so “Chief Architect” involvement from Vern Watts. Watts seems to pretty much have been Mr. IMS for the past four decades, and thus surely knows a whole lot about pointer-based database management systems; presumably, he’s responsible for the generic DBMS design features that are being added to the innovative indexing scheme. On ScaleDB’s advisory board is PeopleSoft veteran Rick Berquist, about whom I’ve had fond thoughts ever since he talked me into focusing on consulting as the core of my business.*
*More precisely, Rick pretty much tricked me into doing a day of consulting for $15K, then revealed that’s what he’d done, expressing the thought that he’d very much gotten his money’s worth. But I digress …
ScaleDB has no customers to date, but hopes to be in beta by the end of this year. Angels and a small VC firm have provided bridge loans; otherwise, ScaleDB has no outside investment. ScaleDB’s business model thoughts include: Read more
| Categories: Data models and architecture, Mid-range, MySQL, OLTP, Open source, ScaleDB, Theory and architecture | 5 Comments |
Supporting evidence for the DBMS disruption story
As previously announced, I did a webcast this afternoon, discussing database diversity. The title of the talk was taken directly from a post – What leading DBMS vendors don’t want you to realize — that argued mid-range DBMS are suitable for a broad variety of tasks. The overriding theme was a Clayton Christensen-style “disruption” narrative.
The sponsor was EnterpriseDB, which is fitting. While not the biggest DBMS industry disrupter in terms of revenue or visible impact (MySQL and Netezza say “Hi”), the Postgres family in general and EnterpriseDB in particular epitomize the disruption threat like nobody else, because of how broadly they substitute for market-leading database managers.
As I promised on the call, below is a post with links to further research backing up the points made. They’re numbered to match some of the presentation slides, which you can find at this link.
3. Much of the discussion of database diversity comes from a series of posts I coordinated with Mike Stonebraker.
4. At various times, starting on Slide 4, I made reference to datatype extensibility, a key feature of Oracle and DB2 – and a key advantage of Postgres over MySQL.
10. Capping off the database diversity discussion, Slide 10 mirrors this 11-point version of a data management software taxonomy.
13-14. I’ve posted many times about data warehousing DBMS and related technologies, including this overview of major analytic DBMS products, another recent overview of data warehouse specialty technologies, and an attempt to distinguish between data warehouse appliance myths and realities. Of particular interest for further research may be our sections on data warehouse appliances and columnar DBMS.
15. I do most of my posting about text search over on Text Technologies, specifically in the search category. Vendors I specifically mentioned as blending search with other kinds of data retrieval were Mark Logic and Attivio.
16. There’s a section here on native XML database management.
17. We also have a section on managing RDF and other graphical data models.
18. Ditto complex event/stream processing.
19. The only embeddable DBMS I’ve written much about recently is solidDB. And frankly, even in that case I’ve focused more on mid-tier caching uses, the now-canceled MySQL relationship, or general technology than I did specifically on embedded uses.
22-24. Back in February, 2007 I made what is probably still my clearest post explaining why I think market-leading DBMS vendors are in the process of getting disrupted
| Categories: EnterpriseDB and Postgres Plus, Mid-range, MySQL, Open source, Oracle, PostgreSQL | Leave a Comment |
My own data management software taxonomy
On a recent webcast, I presented an 11-node data management software taxonomy, updating a post commenting on Mike Stonebraker’s. It goes:
1. High-end OLTP/general-purpose DBMS
2. Mid-range OLTP/general-purpose DBMS
3. Row-based analytic RDBMS
4. Column- or array-based analytic RDBMS
5. Text search engines
6. XML and OO DBMS (but these may merge with search)
7. RDF and other graphical DBMS (but these may merge with relational)
8. Event/stream processing engines (aka CEP)
9. Embedded DBMS for devices
10. Sub-DBMS file managers (e.g. MapReduce/Hadoop)
11. Science DBMS
Obviously, this is a work in progress. In particular, while there’s clearly more than one kind of analytic DBMS, partitioning them into categories is not easy.
| Categories: Database diversity | 5 Comments |
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.
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, Kickfire, MySQL | 7 Comments |
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:
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Sun partners with both Greenplum and ParAccel.
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HP sells Neoview, and also is partnered with Vertica.
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EMC (together with Dell in North America and Bull in Europe) sells DATAllegro. Now EMC is also entering a partnership with ParAccel.
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Teradata is pretty far down the road toward releasing a low-end product.
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
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, EMC, ParAccel | 2 Comments |