DBMS product categories
Analysis of database management technology in specific product categories. Related subjects include:
Mike Stonebraker’s DBMS taxonomy
In a response to my recent five-part series on DBMS diversity, Mike Stonebraker has proposed his own taxonomy of data management technologies over on Vertica’s Database Column blog. (Edit: Some good stuff disappeared when Vertica nuked that blog.)
- OLTP DBMSs focused on fast, reliable transaction processing
- Analytic/Data Warehouse DBMSs focused on efficient load and ad-hoc query performance
- Science DBMSs — after all MatLab does not scale to disk-sized arrays
- RDF stores focused on efficiently storing semi-structured data in this format
- XML stores focused on semi-structured data in this format
- Search engines — the big players all use proprietary engines in this area
- Stream Processing Engines focused on real-time StreamSQL
- “Lean and Mean,” less-than-a-database engines focused on doing a small number of things very well (embedded databases are probably in this category)
- MapReduce and Hadoop — after all Google has enough “throw weight” to define a category
He goes on to say that each will be architected differently, except that — as he already convinced me back in July — RDF will be well-managed by specialty data warehouse DBMS. Read more
| Categories: Data types, Database diversity, Michael Stonebraker, Mid-range, OLTP, RDF and graphs, Theory and architecture | 6 Comments |
Database management system choices — mid-range-relational
This is the fourth of a five-part series on database management system choices. For the first post in the series, please click here.
The other threat to the high-end relational DBMS vendors aims squarely at the heart of their business. It’s the mid-range relational database management systems, which are doing an ever-larger fraction of what their high-end cousins can. That said, different products do different things well. So if you’re not blindly paying up for the security of an all-things-to-all-people high-end DBMS, there are a number of factors you might want to consider.
| Categories: Database diversity, EnterpriseDB and Postgres Plus, Mid-range, MySQL, OLTP, PostgreSQL, Theory and architecture | 3 Comments |
Database management system choices – relational data warehouse
This is the third of a five-part series on database management system choices. For the first post in the series, please click here.
High-end OLTP relational database management system vendors try to offer one-stop shopping for almost all data management needs. But as I noted in my prior post, their product category is facing two major competitive threats. One comes from specialty data warehouse database management system products. I’ve covered those extensively in this blog, with key takeaways including:
- Specialty data warehouse products offer huge cost advantages versus less targeted DBMS. This applies to purchase/maintenance and administrative costs alike. And it’s true even when the general-purposed DBMS boast data warehousing features such as star indexes, bitmap indexes, or sophisticated optimizers.
- The larger the database, the bigger the difference. It’s almost inconceivable to use Oracle for a 100+ terabyte data warehouse. But if you only have 5 terabytes, Oracle is a perfectly viable – albeit annoying and costly – alternative.
- Most specialty data warehouse products have a shared-nothing architecture. Smaller parts are cheaper per unit of capacity. Hence shared nothing/grid architectures are inherently cheaper, at least in theory. In data warehousing, that theoretical possibility has long been made practical.
- Specialty data warehouse products with row-based architectures are commonly sold in appliance formats. In particular, this is true of Teradata, Netezza, DATAllegro, and Greenplum. One reason is that they’re optimized to stream data off of disk fairly sequentially, as opposed to relying on random seeks.
- Specialty data warehouse products with columnar architectures are commonly available in software-only formats. Even so, Vertica and ParAccel also boast appliance deals, with HP and Sun respectively.
- There is tremendous technical diversity and differentiation in the specialty data warehouse system market.
Let me expand on that last point. Different features may or may not be important to you, depending on whether your precise application needs include: Read more
| Categories: Analytic technologies, Data warehouse appliances, Data warehousing, Database diversity, Theory and architecture | 20 Comments |
Database management system choices – 4 categories of relational
This is the second of a five-part series on database management system choices. For the first post in the series, please click here.
For the most part, relational database management systems divide into four major classes:
- High-end OLTP (OnLine Transaction Processing) relational DBMS. Oracle is the flagship for this category, followed by DB2.
- Specialty data warehouse DBMS. Teradata is the leader here, followed by Netezza, DATAllegro, ParAccel, Vertica, Infobright, Greenplum, Kognitio, Sybase IQ, and a host of others.
- Mid-range relational database management systems. Most of the contenders here fall into one or more of three categories: Open-source-based relational DBMS (MySQL, PostgreSQL, EnterpriseDB); reseller-focused relational DBMS (Progress OpenEdge, Pervasive PSQL); or crippled “editions” of high-end systems. Microsoft SQL Server was once a clear mid-range system, but now is better classified as high-end OLTP.
- Embedded relational database management systems. The leader of this category is Sybase’s SQL Anywhere. Also significant are memory-centric products Oracle TimesTen and solidDB.
| Categories: Database diversity, OLTP, Theory and architecture | 9 Comments |
EnterpriseDB on Elastra, early stages
I finally caught up with Bob Zurek about EnterpriseDB’s foray into the Elastra cloud. Here are some highlights:
- There have been dozens of applicants for the EnterpriseDB/Elastra beta program. As is usual in limited beta programs, EnterpriseDB is trying to sort out the ones who’ll make a big commitment from the tire-kickers.
- The main interest in EnterpriseDB/Elastra has come from ISVs, and secondarily from purely online businesses (e.g., SaaS vendors, web businesses, and a large MMO game vendor). There’s been a little interest from enterprises.
- Significant fractions of the EnterpriseDB/Elastra beta applications come from each of the Oracle, PostgreSQL, and MySQL user communities. A few come from SQL Server. None come from DB2.
- Bob praised Elastra for its technology in clustering, starting/stopping instances, etc. He also said that EnterpriseDB had “educated” Elastra on EnterpriseDB internals and/or admin tools, to make the integration work.
- EnterpriseDB will start turning on a few beta Elastra customers any day now (i.e., it may well not take until March, the original target).
| Categories: Cloud computing, Elastra, EnterpriseDB and Postgres Plus, Mid-range, OLTP, Open source | Leave a Comment |
PostgreSQL speeds up OLTP
The Register reports on PostgreSQL 8.3, and emphasizes OLTP speedups and reductions in administrative burden:
Among the changes, Heap Only Tuples (HOT) that may cut the maintenance overhead of frequently updated tables by up to 75 per cent, spread checkpoints and background writer autotuning to reduce the impact of check points on response times, and an asynchronous commit option that also speeds the response times of certain transactions.
I wonder how EnterpriseDB compares on these features.
Edit: Slashdot has discussion and links. And here’s a PostgreSQL feature matrix.
| Categories: EnterpriseDB and Postgres Plus, Mid-range, OLTP, Open source, PostgreSQL | 1 Comment |
Why not database SaaS?
After a flurry of recent announcements of database SaaS (Software as a Service), eWeek has published a backlash article. The angle is that database SaaS is too expensive, because you can get decent DBMS for free and per-gig usage charges might be expensive for big databases.
I think that’s missing the point. Most OLTP databases are pretty small. Or, if they’re big, they get that way through a lot of transactions. In the first case, hosted management is cheap. In the second case, hosted management is taking care of a large burden for you. Read more
| Categories: Kognitio, OLTP, Software as a Service (SaaS) | 2 Comments |
EnterpriseDB joins Elastra in the Amazon cloud
When Elastra announced their service to host MySQL and PostgreSQL in the Amazon S3/EC2 cloud, I immediately told my dear darling clients at EnterpriseDB they should do the same. Whereupon they told me it would happen soon. However, they neglected to tell me when it was actually announced. So I know no more than can be found in this Computerworld article.
But I’ll say this — it’s a very tempting option, both for new web-based applications or businesses, or simply as a development platform pending later redeployment.
| Categories: Amazon and its cloud, Cloud computing, Elastra, EnterpriseDB and Postgres Plus, Mid-range, OLTP, Open source, Software as a Service (SaaS) | 2 Comments |
What hard-core transactional applications have actually been built in MySQL, PostgreSQL, EnterpriseDB, or FileMaker?
And here’s the biggie.
Question of the day #3
What complex, high-volume transactional applications have actually been built in mid-range DBMS such as MySQL, PostgreSQL, FileMaker, or EnterpriseDB?
I’ve been flamed for suggesting that MySQL or FileMaker aren’t fully equal to Oracle and DB2 in supporting hard-core transactional applications. (Which is ironic, because I’ve also been flamed for suggesting hard-core transactional support isn’t as big a deal for DBMS selection as some relational purists insist. But I digress …) So I’m putting the question out there — what impressive transactional applications do the stand-alone mid-range DBMS actually support? Read more
| Categories: EnterpriseDB and Postgres Plus, FileMaker, Mid-range, MySQL, OLTP, Open source, PostgreSQL | 20 Comments |
Kognitio WX2 overview
I had a call today with Kognitio execs Paul Groom and John Thompson. Hopefully I can now clear up some confusion that was created in this comment thread. (Most of what I wrote about Kognitio in October, 2006 still applies.) Here are some highlights. Read more