XtremeData update
I talked with Geno Valente of XtremeData tonight. Highlights included:
- XtremeData still hasn’t sold any dbX stuff (they’ve had a side business in generic FPGA-based boards paying the bills for years). Well, there may have been some paid POCs (proofs of concept) or something, but real sales haven’t come through yet.
- XtremeData does have three prospects who have said “Yes”, and expects one order to come through this month.
- XtremeData continues to believe it shines when:
- Data models are complex
- In particular, there are complex joins
- In particular, two large tables have to be joined with each other, under circumstances where no product can avoid doing vast data redistribution
- XtremeData insists that all the nice things Bill Inmon – including in webinars — has said about it has not been for pay or other similar business compensation. That’s quite unusual.
- XtremeData is coming out with a new product, codenamed the Personal Data Warehouse (PDW), which:
- Is ready to go into beta test
- Should be launched in a month and a half or so
- Will have a different name when it is launched
Naming aside, Read more
| Categories: Analytic technologies, Benchmarks and POCs, Data warehouse appliances, Data warehousing, Database compression, Kickfire, Market share, Netezza, Pricing, XtremeData | Leave a Comment |
Toward a NoSQL taxonomy
I talked Friday with Dwight Merriman, founder of 10gen (the MongoDB company). He more or less convinced me of his definition of NoSQL systems, which in my adaptation goes:
NoSQL = HVSP (High Volume Simple Processing) without joins or explicit transactions
Within that realm, Dwight offered a two-part taxonomy of NoSQL systems, according to their data model and replication/sharding strategy. I’d be happier, however, with at least three parts to the taxonomy:
- How data looks logically on a single node
- How data is stored physically on a single node
- How data is distributed, replicated, and reconciled across multiple nodes, and whether applications have to be aware of how the data is partitioned among nodes/shards. Read more
| Categories: Cassandra, Data models and architecture, NoSQL, Parallelization, RDF and graphs, Structured documents, Theory and architecture | 4 Comments |
The Naming of the Foo
Let’s start from some reasonable premises. Read more
| Categories: Data models and architecture, Database diversity, Hadoop, MapReduce, Mark Logic, NoSQL, OLTP, Theory and architecture | 25 Comments |
Some NoSQL links
I plan to post a few things soon about MongoDB, Cassandra, and NoSQL in general. So I’m poking around a bit reading stuff on the subjects. Here are some links I found. Read more
| Categories: Amazon and its cloud, Cassandra, Continuent, Google, MySQL, NoSQL, Open source, RDF and graphs, Tokutek | 5 Comments |
Cassandra and the NoSQL scalable OLTP argument
Todd Hoff put up a provocative post on High Scalability called MySQL and Memcached: End of an Era? The post itself focuses on observations like:
- Facebook invented and is adopting Cassandra.
- Twitter is adopting Cassandra.
- Digg is adopting Cassandra.
- LinkedIn invented and is adopting Voldemort.
- Gee, it seems as if the super-scalable website biz has moved beyond MySQL/Memcached.
But in addition, he provides a lot of useful links, which DBMS-oriented folks such as myself might have previously overlooked. Read more
| Categories: Cassandra, Data models and architecture, NoSQL, OLTP, Open source, Parallelization, Specific users, Theory and architecture | 11 Comments |
Another reason to expect number-crunching and big-data management to converge
Dan Olds argues that Oracle is likely to pursue commercially-substantive high performance computing (HPC), emphasis mine: Read more
| Categories: Analytic technologies, Data warehousing, Exadata, Oracle, Theory and architecture | Leave a Comment |
Notes on Sybase Adaptive Server Enterprise
It had been a very long time since I was remotely up to speed on Sybase’s main OLTP DBMS, Adaptive Server Enterprise (ASE). Raj Rathee, however, was kind enough to fill me in a few days ago. Highlights of our chat included: Read more
| Categories: Cache, In-memory DBMS, Memory-centric data management, Sybase | Leave a Comment |
February 2010 data warehouse DBMS news roundup
February is usually a busy month for data warehouse DBMS product releases, product announcements, and other real or contrived data warehouse DBMS news, and it can get pretty confusing trying to keep those categories of “news” apart.* This year is no exception, although several vendors – including Teradata and Netezza – are taking “rolling thunder” approaches, doing some of their announcements this month while holding others back for March or April.
*I probably have it worse than most people in that regard, because my clients run tentative feature lists and announcement schedules by me well in advance, which may get changed multiple times before the final dates roll around. I also occasionally miss some detail, if it wasn’t in a pre-briefing but gets added at the end.
Anyhow, the three big themes of this month’s announcements are probably:
- Integrating different kinds of analytic processing into databases and DBMS.
- Taking advantage of hardware advances.
- Playing catchup in areas where small vendors’ products weren’t mature yet.
| Categories: Analytic technologies, Aster Data, Data warehousing, Netezza, Teradata, Vertica Systems | Leave a Comment |
TwinFin(i) – Netezza’s version of a parallel analytic platform
Much like Aster Data did in Aster 4.0 and now Aster 4.5, Netezza is announcing a general parallel big data analytic platform strategy. It is called Netezza TwinFin(i), it is a chargeable option for the Netezza TwinFin appliance, and many announced details are on the vague side, with Netezza promising more clarity at or before its Enzee Universe conference in June. At a high level, the Aster and Netezza approaches compare/contrast as follows: Read more
| Categories: Analytic technologies, Aster Data, Data warehouse appliances, Data warehousing, Hadoop, MapReduce, Netezza, SAS Institute, Teradata | 2 Comments |
Aster Data nCluster 4.5
Like Vertica, Netezza, and Teradata, Aster is using this week to pre-announce a forthcoming product release, Aster Data nCluster 4.5. Aster is really hanging its identity on “Big Data Analytics” or some variant of that concept, and so the two major named parts of Aster nCluster 4.5 are:
- Aster Data Analytic Foundation, a set of analytic packages prebuilt in Aster’s SQL-MapReduce
- Aster Data Developer Express, an Eclipse-based IDE (Integrated Development Environment) for developing and testing applications built on Aster nCluster, Aster SQL-MapReduce, and Aster Data Analytic Foundation
And in other Aster news:
- Along with the development GUI in Aster nCluster 4.5, there is also a new administrative GUI.
- Aster has certified that nCluster works with Fusion I/O boards, because at least one retail industry prospect cares. However, that in no way means that arm’s-length Fusion I/O certification is Aster’s ultimate solid-state memory strategy.
- I had the wrong impression about how far Aster/SAS integration has gotten. So far, it’s just at the connector level.
Aster Data Developer Express evidently does some cool stuff, like providing some sort of parallelism testing right on your desktop. It also generates lots of stub code, saving humans from the tedium of doing that. Useful, obviously.
But mainly, I want to write about the analytic packages. Read more