Comments on: Aster Data enters the appliance game

By: Correction to a recent quote | DBMS2 -- DataBase Management System Services

Correction to a recent quote | DBMS2 -- DataBase Management System Services — Wed, 01 Jul 2009 06:19:19 +0000

[...] quoted in a recent article around Aster’s appliance announcement as saying data warehouse appliances are more suitable for small workgroups of analysts crunching [...]

By: Curt Monash

Curt Monash — Wed, 01 Jul 2009 06:03:10 +0000

Steve,

Of course, that assumes equal or better throughput per unit of processing power.

By: Steve Wooledge

Steve Wooledge — Wed, 01 Jul 2009 05:11:31 +0000

Dave-

We focused our comparison on large-scale MPP DW appliances who like to point out the “amount” of data they can store in marketing claims: peta-, exa-, … “Xtreme-ginormous” to make a strong contrast. Our point is to focus the discussion on processing power per TB of storage, which is a better measure of the value someone can get from their data. Having processing power plus SQL/MapReduce in-database for rich analytic expressions is where we see the future of data warehousing: http://www.asterdata.com/mapreduce

By: Dave Menninger

Dave Menninger — Tue, 30 Jun 2009 16:51:17 +0000

Steve–We agree wholeheartedly that it’s good to deliver different deployment options to customers. Vertica was the 1st to offer four deployment options–software only from the beginning in Q1 2007; appliance on HP hardware in Dec 2007; Amazon cloud in May 2008 and VMware appliance in Feb 2009. But I’m not sure I agree that you offer the most cost-effective MPP data warehouse appliance. Your positioning graphic omits all the columnar appliances…from Vertica, ParAccel, Sybase, et al, which typically offer faster performance on less hardware due to compression, columnar storage and other IO-reducing advantages.

By: Curt Monash

Curt Monash — Tue, 30 Jun 2009 01:16:27 +0000

Greg,

You SLIGHTLY rephrased and improved upon my reasoning for demonstrating that the ParAccel TPC-H filing is “absurdly unrealistic” as a guide to DBMS selection, and a blight upon the industry. Thank you for your assistance.

That you phrased that as if you were being critical of and disagreeing with me is baffling — unless, of course, that wasn’t your point at all. But if so, you either haven’t made your point clear or else haven’t done much in the way of substantiating it.

Best,

CAM

By: Greg Rahn

Greg Rahn — Tue, 30 Jun 2009 01:11:07 +0000

@Curt

Based on your response I would say you missed my point. Also it seems things are relevant/irrelevant with you which of course is also a misunderstanding. Let me also be clear that I think most TPC hardware configurations (the ones that focus purely on performance vs. price/performance) are significantly different from what production customers would run, so there is no point in trying to argue with me there either.

I think that only mentioning (disk capacity)/(user data) w/o including the number of drives uses is just plucking numbers out of context as simply increasing/decreasing this ratio (but holding the spindle count constant) for a given system would have minimal impact on the performance of it. However, if the spindle count changes significantly, but total capacity is constant, then performance will likely significantly change as well.

Hopefully that clarifies the point I was trying to make. If not, it will have to suffice…as Karl from Kickfire cited a TPC-H result and I’m running for cover.

By: Steve Wooledge

Steve Wooledge — Mon, 29 Jun 2009 23:18:43 +0000

As a point of clarification, we don’t view the data warehousing world as “either-or” / “black-white”. Some customers want software, others want appliances, still others want a cloud-based DBMS. It is our responsibility to give to each customer the best offering on each of these packaged frameworks that works best for them. The importance of today’s announcement is that we are bringing the most cost-effective MPP data warehouse appliance to customers.

Additionally, we’ve had lots of requests from customers for a “starter kit”, including people evaluating Hadoop, but who want enterprise-class features before bringing MapReduce into their environment. This is why a $50k price point made sense. More thoughts here:http://www.asterdata.com/blog/index.php/2009/06/29/enterprise-ready-mapreduce-data-warehouse-appliance/

By: Karl

Karl — Mon, 29 Jun 2009 20:04:36 +0000

Interesting thread. We applaud Aster’s move to appliances. It is a proven delivery model, particularly for the mass market. This is where Kickfire is focused: http://tinyurl.com/ljg2sx. With appliances starting at $32k for 1TB capacity and the world’s #1 price/performance per independent industry benchmarks (http://tinyurl.com/52zyno), the Kickfire appliance opens up the possibility of high-end data warehousing for customers who previously could not afford this capability.

By: Curt Monash

Curt Monash — Mon, 29 Jun 2009 19:51:15 +0000

Greg,

If you’d rather talk about spindles because you think TB/spindle is irrelevant, fine. The ParAccel configuration was way out of whack in number of spindles as well.

By: Steve Wooledge

Steve Wooledge — Mon, 29 Jun 2009 18:55:07 +0000

Curt,

The configurations for the Aster MapReduce DW Appliance product line are all for *uncompressed* data, except for the 1 petabyte appliance: http://www.asterdata.com/resources/downloads/datasheets/appliance_ds.pdf