Aster Data enters the appliance game
Aster Data is rolling out a line of nCluster appliances today. Highlights include:
- Configurations ranging from 9 6.25 terabytes to 1 petabyte of user data. (Edit: Here’s the up-to-date data sheet.)
- A $50K “Express Edition” price for <1 terabyte of user data. Unfortunately, that’s the only stated price.
- The option of bundled MicroStrategy.
- “MapReduce” in the name, which suggests something about the positioning — i.e., enterprise decision support, rather than Aster’s usual web/”frontline” emphasis. (Edit: That also fits with Aster’s recent MapReduce-for-.NET announcement.) (Edit: Actual name is Aster MapReduce Data Warehouse Appliance.)
- Claims that because Aster runs effectively on cheaper, more truly “commodity” hardware than competitors, you get more hardware bang for the buck if you buy from Aster.
I don’t have a lot more to add right now, mainly because I wrote at some length about Aster’s non-appliance-specific, non-MapReduce technology and positioning a couple of weeks ago.
| Categories: Analytic technologies, Aster Data, Business intelligence, Data warehouse appliances, Data warehousing, Database compression, MapReduce, Pricing | 16 Comments |
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.
| Categories: About this blog, Aster Data, Data warehousing, Greenplum, Infobright, Kickfire, Microsoft and SQL*Server, Netezza, Sybase, Teradata, Vertica Systems | 4 Comments |
ParAccel pricing
As I noted in connection with ParAccel’s recent TPC-H filing, I think the whole exercise is basically an expensive joke. But one slightly useful spin-off is that ParAccel disclosed pricing. Specifically, ParAccel’s stated price in the disclosure document is:
- $100,000/TB license fee (user data). That’s like Vertica, although I don’t know whether ParAccel emulates Vertica’s policy of making test and development licenses free.
- 57% quantity discount at 30 terabytes. That’s not surprising.
- 1% annual maintenance fee (applied to the discounted price). That’s astounding.
Last year ParAccel quoted prices of $100,000/TB or $50,000/server. The latter figure would seem to have led to lower numbers on the benchmark configuration, so perhaps it’s no longer an option on ParAccel’s price list.
| Categories: Benchmarks and POCs, Data warehousing, ParAccel, Pricing | 3 Comments |
The TPC-H benchmark is a blight upon the industry
ParAccel has released a 30,000-gigabtye TPC-H benchmark, and no less a sage than Merv Adrian paid attention. Now, the TPCs may have had some use in the 1990s. Indeed, Merv was my analyst relations contact for a visit to my clients at Sybase around the time — 1996 or so — I was advising Sybase on how to market against its poor benchmark results. But TPCs are worthless today.
It’s not just that TPCs are highly tuned (ParAccel’s claim of “load-and-go” is laughable Edit: Looking at Appendix A of the full disclosure report, maybe it’s more justified than I thought.). It’s also not just that different analytic database management products perform very differently on different workloads, making the TPC-H not much of an indicator of anything real-life. The biggest problem is: Most TPC benchmarks are run on absurdly unrealistic hardware configurations.
For example, if you look at some details, the ParAccel 30-terabyte benchmark ran on 43 nodes, each with 64 gigabytes of RAM and 24 terabytes of disk. That’s 961,124.9 gigabytes of disk, officially, for a 32:1 disk/data ratio. By way of contrast, real-life analytic DBMS with good compression often have disk/data ratios of well under 1:1.
Meanwhile, the RAM:data ratio is around 1:11 It’s clear that ParAccel’s early TPC-H benchmarks ran entirely in RAM; indeed, ParAccel even admits that. And so I conjecture that ParAccel’s latest TPC-H benchmark ran (almost) entirely in RAM as well. Once again, this would illustrate that the TPC-H is irrelevant to judging an analytic DBMS’ real world performance.
More generally — I would not advise anybody to consider ParAccel’s product, for any use, except after a proof-of-concept in which ParAccel was not given the time and opportunity to perform extensive off-site tuning. I tend to feel that way about all analytic DBMS, but it’s a particular concern in the case of ParAccel.
| Categories: Analytic technologies, Benchmarks and POCs, Buying processes, Columnar database management, Data warehousing, Database compression, ParAccel | 96 Comments |
H-Store is now VoltDB
I’ve always honored more of an NDA about the H-Store project and its commercialization than I really felt obligated to, given how freely information was being bandied about to others. I’m still doing so. 🙂
But I think I’ll at least say that the H-Store project is now named VoltDB. The VoltDB website names two individuals — Mike Stonebraker and Andy Palmer — both of whom are founders of Vertica. Job listings on the site are for field engineer and trainer, but not developer, so that suggests something about the project’s/product’s maturity level.
If you have an extreme OLTP need, you should talk to VoltDB. If you don’t have access to Mike or Andy directly, I can hook you up with a key VoltDB marketing/outreach guy. Price may not be as much of a barrier as you’d initially fear.
If anybody from VoltDB wants to be less cloak-and-daggery and say more in the comment thread, I’d be pleased.
And yes — an open-secret working name for H-Store/VoltDB was, for a while, “Horizontica.”
| Categories: In-memory DBMS, Memory-centric data management, OLTP, Vertica Systems, VoltDB and H-Store | 15 Comments |
Apparent turmoil at EnterpriseDB
EnterpriseDB seems to be facing a string of management departures:
- Bob Zurek, EnterpriseDB’s well-regarded CTO, is gone. (He landed at Infobright, after a stint of independent consulting.)
- Multiple rumors have founder Andy Astor leaving EnterpriseDB, and stepping back to an advisory role. One version has Tuesday, June 16 as Andy’s last day. Update: As of Wednesday, June 17, Andy Astor is no longer listed as being on EnterpriseDB’s management team.
- Fred Holahan, who was briefly VP of Marketing, is not listed on EnterpriseDB’s management team web page. And EnterpriseDB announced a new VP of Marketing and Product Management on May 21.
- Other rumors point to turmoil at EnterpriseDB as well.
And by the way, EnterpriseDB, which used to call itself “the Oracle-compatible database company,” recently licensed out what used to be its core differentiating technology.
Now, this isn’t all bad news. EnterpriseDB’s Oracle-compatibility focus had to be changed anyway. And Fred Holahan was the proximate cause for me writing:
my recent dealings with EnterpriseDB underscore the importance of being VERY careful about counting your fingers after you shake hands with that company,
Still, these aren’t exactly indicators of a company executing on a smooth-running plan.
| Categories: EnterpriseDB and Postgres Plus, Open source | 3 Comments |
Aster Data on parallelism
Aster Data’s core claim boils down to “We do parallelism better.” Aster has shied away from saying that for marketing purposes, for fear of the response “Yeah, right, everybody says that.” But when I talked with Mayank Bawa, Steve Wooledge, et al. yesterday, I focused discussions on just that point. Based on that chat and others before, here are some highlights (as I understand them) of what Aster claims, believes, or believes to be differentiated about its nCluster technology: Read more
| Categories: Analytic technologies, Aster Data, Data warehousing, MapReduce, Parallelization, Theory and architecture | 3 Comments |
An example of what’s wrong with big vendors’ approaches to BI (SAP in this case)
I just found Chris Kanaracus’ article about SAP’s rollout last month of its “clear enterprises” strategy. The money quote comes from Sara Lee, the user SAP seems to have trotted out:
But Sara Lee has not yet decided to purchase the software, and there are substantial underlying tasks to perform as well, he added.
“This is giving us the horsepower [to analyze data] but we need to have harmonized and structured data underneath it.”
This is from the leading test user of the product?
Business intelligence and the associated data management processes need to be reimagined, and I’m increasingly coming to suspect that the big BI conglomerates aren’t up to the task.
| Categories: Analytic technologies, Business intelligence, SAP AG, Specific users, Theory and architecture | Leave a Comment |
Google Fusion Tables
Google has announced an experimental cloud-based data management system called Fusion Tables. A press article and Slashdot thread ensued, based on some bizarre-sounding analyst quotes that I will not attempt to parse.
What Fusion Tables really seems to be is a spreadsheet without the formulae. That is, it’s a place to dump data in a grid of cells, comment on it, version it, and do elementary data manipulation. This could, I guess, be useful as an alternative to traditional RDBMS — assuming, of course, that you want to have a row-by-row debate about 100 megs of data.
Seriously, while Google Fusion Tables bears some vague resemblance to what I’m thinking about for the future of both business intelligence and data marts, it sounds as if it has a long way to go before it’s something most enterprises should spend time looking at.
| Categories: Analytic technologies, Google, Theory and architecture | 1 Comment |
MMO games are still screwed up in their database technology
Two years ago I wrote about the database technology of Guild Wars. Not coincidentally, Guild Wars was the MMO RPG (Massively Multiplayer Online Role-Playing Game) I then played. I had the chance to interview Guild Wars’ lead developers. While much else they had to say was impressive, Guild Wars’ database architecture was — er, it was rather mind-boggling.
Since then, Linda and I have taken to playing Lord of the Rings Online, commonly known as LOTRO, developed by Turbine, Inc.. I haven’t had the chance to interview any Turbine folks, despite repeated requests. But from afar, it would seem that Turbine’s technology choices leave quite a bit to be desired, in enterprise-like IT areas such as authentication, database management, and storage.
LOTRO and other Turbine games commonly are down, for scheduled maintenance or in some cases otherwise. There is scheduled multi-hour downtime to start many weeks. There are fairly frequent server restarts in addition to that. Lag and congestion are frequent. And so on and so forth. By way of contrast, Guild Wars very rarely goes down, and other technical difficulties are less common as well. Reliability is a key design goal for Guild Wars’ developers, and in my opinion they’ve achieved it.
Some of the reasons for Turbine’s difficulties seem related to the stresses of MMOs — e.g., they’re probably due to the problems caused by having many fictional characters moving through the same fictional space at once, with graphical detail much richer than Guild Wars’. But a couple of head-scratchers make me really wonder about how Turbine manages data. Read more
| Categories: Fun stuff, Games and virtual worlds, Specific users | 18 Comments |