Exasol
Analysis of data warehouse DBMS vendor Exasol. Related subjects include:
Draft slides on how to select an analytic DBMS
I need to finalize an already-too-long slide deck on how to select an analytic DBMS by late Thursday night. Anybody see something I’m overlooking, or just plain got wrong?
Edit: The slides have now been finalized.
Dividing the data warehousing work among MPP nodes
I talk with lots of vendors of MPP data warehouse DBMS. I’ve now heard enough different approaches to MPP architecture that I think it might be interesting to contrast some of the alternatives.
| Categories: Aster Data, Calpont, Exasol, Greenplum, Parallelization, Theory and architecture, Vertica Systems | 22 Comments |
Exasol technical briefing
It took 5 ½ months after my non-technical introduction, but I finally got a briefing from Exasol’s technical folks (specifically, the very helpful Mathias Golombek and Carsten Weidmann). Here are some highlights: Read more
| Categories: Analytic technologies, Benchmarks and POCs, Columnar database management, Data warehousing, Exasol, In-memory DBMS, Memory-centric data management, Pricing | 1 Comment |
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 |
Introduction to Exasol
I had a non-technical introduction today to Exasol, a data warehouse specialist that has gotten a little buzz recently for publishing TPC-H results even faster than ParAccel’s. Here are some highlights:
- Exasol was founded back in 2000.
- Exasol is a German company, with 60 employees. While I didn’t ask, the vast majority are surely German.
- Exasol has two customers. 6-8 more are Coming Real Soon. Most or all of those are in Germany, although one may be in Asia.
- Karstadt (big German retailer) has had Exasol deployed for 3 years. The other deployed customer is the German subsidiary of data provider IMS Health.
- [Redacted for confidentiality] is a strategic investor in and partner of Exasol. [Redacted for confidentiality]’s only competing partnership is with Oracle.
- Exasol’s system is more completely written from scratch than many. E.g., all they use from Linux are some drivers, and maybe a microkernel.
- Exasol runs in-memory. There doesn’t seem to be a disk-centric mode.
- Exasol’s data access methods are sort of like columnar, but not exactly. I look forward to a more technical discussion to sort that out.
- Exasol’s claimed typical compression is 5-7X. As in the Vertica story, database operations are carried out on compressed data.
- Exasol says it has performed a very fast TPC-H inhouse at the 30 terabyte level. However, its deployed sites are probably a lot smaller than that. IMS Health is cited in its literature as 145 gigabytes.
- Oracle and Microsoft are listed as Exasol partners, so there may be some kind of plug-compatibility or back-end processing story.
| Categories: Analytic technologies, Data warehousing, Exasol, Specific users | Leave a Comment |