ParAccel
Analysis of columnar data warehouse DBMS vendor ParAccel, maker of PADB (ParAccel Analytic DataBase). Related subjects include:
My current customer list among the data warehouse specialists
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 data warehouse DBMS/appliance specialists in the group. They are:
- Aster Data
- Calpont
- DATAllegro
- Greenplum
- Infobright
- Netezza
- ParAccel
- Teradata
- Vertica
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, Calpont, Data warehousing, DATAllegro, Greenplum, Infobright, Netezza, ParAccel, Teradata, Vertica Systems | 3 Comments |
Compare/constrast of Vertica, ParAccel, and Exasol
I talked with Exasol today – at 5:00 am! — and of course want to blog about it. For clarity, I’d like to start by comparing/contrasting the fundamental data structures at Vertica, ParAccel, and Exasol. And it feels like that should be a separate post. So here goes.
- Exasol, Vertica, and ParAccel all store data in columnar formats.
- Exasol, Vertica, and ParAccel all compress data heavily.
- Exasol and Vertica operate on in-memory data in compressed formats. ParAccel decompresses the data when it gets to RAM. Exasol, Vertica, and ParAccel all — perhaps to varying extents — operate on in-memory data in compressed formats.
- ParAccel and Exasol write data to what amounts to the in-memory part of their basic data structures; the data then gets persisted to disk. Vertica, however, has a separate in-memory data structure to accept data and write it to disk.
- Vertica is a disk-centric system that doesn’t rely on there being a lot of RAM.
- ParAccel can be described that way too; however, in some cases (including on the TPC-H benchmarks), ParAccel recommends loading all your data into RAM for maximum performance.
- Exasol is totally optimized for the assumption that queries will be run against data that had already been previously loaded into RAM.
Beyond the above, I plan to discuss in a separate post how Exasol does MPP shared-nothing software-only columnar data warehouse database management differently than Vertica and ParAccel do shared-nothing software-only columnar data warehouse database management. 🙂
| Categories: Columnar database management, Data warehousing, Database compression, Exasol, ParAccel, Vertica Systems | 12 Comments |
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
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, DATAllegro, Greenplum, Microsoft and SQL*Server, Oracle, ParAccel, Teradata, Vertica Systems | 15 Comments |
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.
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, EMC, ParAccel, Parallelization | 2 Comments |
ParAccel pricing
I made a round of queries about data warehouse software or appliance pricing, and am posting the results as I get them. Earlier installments featured Teradata and Netezza. Now ParAccel is up.
ParAccel’s software license fees are actually very simple — $50K per server or $100K per terabyte, whichever is less. (If you’re wondering how the per-TB fee can ever be the smaller one, please recall that ParAccel offers a memory-centric approach to sub-TB databases.)
Details about how much data fits on a node are hard to come by, as is clarity about maintenance costs. Even so, pricing turns out to be one of the rare subjects on which ParAccel is more forthcoming than most competitors.
| Categories: Analytic technologies, Data warehousing, ParAccel, Pricing | 3 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 |
ParAccel technical highlights
I recently caught up with ParAccel’s CTO Barry Zane and Marketing VP Kim Stanick for a long technical discussion, which they have graciously continued by email. It would be impolitic in the extreme to comment on what led up to that. Let’s just note that many things I’ve previously written about ParAccel are now inoperative, and go straight to the highlights.
| Categories: Columnar database management, Data warehousing, Emulation, transparency, portability, Microsoft and SQL*Server, ParAccel | 5 Comments |
Load speeds and related issues in columnar DBMS
Please do not rely on the parts of the post below that are about ParAccel. See our February 18 post about ParAccel instead.
I’ve already posted about a chat I had with Mike Stonebraker regarding Vertica yesterday. I naturally raised the subject of load speed, unaware that Mike’s colleague Stan Zlodnik had posted at length about load speed the day before. Given that post, it seems timely to go into a bit more detail, and in particular to address three questions:
- Can columnar DBMS do operational BI?
- Can columnar DBMS do ELT (Extract-Load-Transform, as opposed to ETL)?
- Are columnar DBMS’ load speeds a problem other than in issues #1 and #2?
Things could get interesting for Infobright
Of the many new specialty data warehouse DBMS and appliances, Infobright’s BrightHouse is the only leading one based on MySQL. I expect Sun and Infobright to have some interesting conversations now. Conversely, I wouldn’t be optimistic about any partnering discussions Infobright might have with, say, HP.
The most directly competitive relationship Sun now has to any future Infobright partnership is with ParAccel.
| Categories: Analytic technologies, Data warehousing, Infobright, MySQL, Open source, ParAccel | 2 Comments |