OLTP
Analysis of database management systems designed with a focus on OTLP (OnLine Transaction Processing) uses.
Two cornerstones of Oracle’s database hardware strategy
After several months of careful optimization, Oracle managed to pick the most inconvenient* day possible for me to get an Exadata update from Juan Loaiza. But the call itself was long and fascinating, with the two main takeaways being:
- Oracle thinks flash memory is the most important hardware technology of the decade, one that could lead to Oracle being “bumped off” if they don’t get it right.
- Juan believes the “bulk” of Oracle’s business will move over to Exadata-like technology over the next 5-10 years. Numbers-wise, this seems to be based more on Exadata being a platform for consolidating an enterprise’s many Oracle databases than it is on Exadata running a few Especially Big Honking Database management tasks.
And by the way, Oracle doesn’t make its storage-tier software available to run on anything than Oracle-designed boxes. At the moment, that means Exadata Versions 1 and 2. Since Exadata is by far Oracle’s best DBMS offering (at least in theory), that means Oracle’s best database offering only runs on specific Oracle-sold hardware platforms. Read more
Intersystems Cache’ highlights
I talked with Robert Nagle of Intersystems last week, and it went better than at least one other Intersystems briefing I’ve had. Intersystems’ main product is Cache’, an object-oriented DBMS introduced in 1997 (before that Intersystems was focused on the fourth-generation programming language M, renamed from MUMPS). Unlike most other OODBMS, Cache’ is used for a lot of stuff one would think an RDBMS would be used for, across all sorts of industries. That said, there’s a distinct health-care focus to Intersystems, in that:
- MUMPS, the original Intersystems technology, was focused on health care.
- The reasons Intersystems went object-oriented have a lot to do with the structure of health-care records.
- Intersystems’ biggest and most visible ISVs are in the health-care area.
- Intersystems is actually beginning to sell an electronic health records system called TrakCare around the world (but not in the US, where it has lots of large competitive VARs).
Note: Intersystems Cache’ is sold mainly through VARs (Value-Added Resellers), aka ISVs/OEMs. I.e., it’s sold by people who write applications on top of it.
So far as I understand – and this is still pretty vague and apt to be partially erroneous – the Intersystems Cache’ technical story goes something like this: Read more
Categories: Data models and architecture, Emulation, transparency, portability, Health care, Intersystems and Cache', Mid-range, Object, OLTP, Sybase, Theory and architecture | 8 Comments |
Boston Big Data Summit keynote outline
Last month, Bob Zurek asked me to give a talk on “Big Data”, where “big” is anything from a few terabytes on up, then moderate a panel on cloud computing. We agreed that I could talk just from notes, without slides. So, since I have them typed up, I’m posting them below.
Thoughts on the integration of OLTP and data warehousing, especially in Exadata 2
Oracle is pushing Exadata 2 as being a great system for any of OLTP (OnLine Transaction Processing), data warehousing or, presumably, the integration of same. This claim rests on a few premises, namely: Read more
Categories: Analytic technologies, Data warehouse appliances, Data warehousing, Exadata, OLTP, Oracle, Solid-state memory, Theory and architecture | 36 Comments |
Notes on the Oracle Database 11g Release 2 white paper
The Oracle Database 11g Release 2 white paper I cited a couple of weeks ago has evidently been edited, given that a phrase I quoted last month is no longer to be found. Anyhow, here are some quotes from and comments on what evidently is the latest version. Read more
The Boston Globe had an article on VoltDB
The Boston Globe article has more detail than Vertica and VoltDB have ever OKed me to put out, and some business details they’ve never given me.
Categories: In-memory DBMS, Memory-centric data management, OLTP, Vertica Systems, VoltDB and H-Store | Leave a Comment |
Groovy Corp puts out a ridiculous press release
I knew Groovy Corp’s press release today would be bad, as it was pitched in advance as being about an awe-inspiring benchmark. That part met my very low expectations, emphasizing how the Groovy SQL Switch massively outperformed MySQL* in a benchmark, and how this supposedly shows the Groovy SQL Switch would outperform every other competitive RDBMS by at least similar margins.
*While a few use cases are exceptions, being “better than MySQL” for a DBMS is basically like being “better than Pabst Blue Ribbon” for a beer. Unless price is your top consideration, why are you even making the comparison?
Even worse, the press release, from its subhead and very first sentence, emphasizes the claim “the Groovy SQL Switch’s ability to significantly outperform relational databases.” As CEO Joe Ward quickly agreed by email, that’s not accurate. As you would expect from the “SQL” in its name, the Groovy SQL Switch is just as relational as the products it’s being contrasted to. Unfortunately for Joe, who I gather aspires to edit it to say something more sensible, the press release is out already in multiple places.
More favorably, Renee Blodgett has a short, laudatory post about Groovy, with some kind of embedded video.
Categories: Groovy Corporation, In-memory DBMS, Memory-centric data management, MySQL, OLTP | 17 Comments |
What are the best choices for scaling Postgres?
March, 2011 edit: In its quaintness, this post is a reminder of just how fast Short Request Processing DBMS technology has been moving ahead. If I had to do it all over again, I’d suggest they use one of the high-performance MySQL options like dbShards, Schooner, or both together. I actually don’t know what they finally decided on in that area. (I do know that for analytic DBMS they chose Vertica.)
I have a client who wants to build a new application with peak update volume of several million transactions per hour. (Their base business is data mart outsourcing, but now they’re building update-heavy technology as well. ) They have a small budget. They’ve been a MySQL shop in the past, but would prefer to contract (not eliminate) their use of MySQL rather than expand it.
My client actually signed a deal for EnterpriseDB’s Postgres Plus Advanced Server and GridSQL, but unwound the transaction quickly. (They say EnterpriseDB was very gracious about the reversal.) There seem to have been two main reasons for the flip-flop. First, it seems that EnterpriseDB’s version of Postgres isn’t up to PostgreSQL’s 8.4 feature set yet, although EnterpriseDB’s timetable for catching up might have tolerable. But GridSQL apparently is further behind yet, with no timetable for up-to-date PostgreSQL compatibility. That was the dealbreaker.
The current base-case plan is to use generic open source PostgreSQL, with scale-out achieved via hand sharding, Hibernate, or … ??? Experience and thoughts along those lines would be much appreciated.
Another option for OLTP performance and scale-out is of course memory-centric options such as VoltDB or the Groovy SQL Switch. But this client’s database is terabyte-scale, so hardware costs could be an issue, as of course could be product maturity.
By the way, a large fraction of these updates will be actual changes, as opposed to new records, in case that matters. I expect that the schema being updated will be very simple — i.e., clearly simpler than in a classic order entry scenario.
The Groovy SQL Switch
I’ve now had a chance to talk with Groovy Corporation CEO Joe Ward, and can add to what Groovy advisor Tony Bain wrote about Groovy Corp and its SQL Switch DBMS. Highlights include: Read more
Categories: Groovy Corporation, In-memory DBMS, Memory-centric data management, OLTP | 2 Comments |
Groovy Corp
Groovy Corp sent over a press release and apparently suggested I write about the company’s wonderfulness immediately. This was without any kind of briefing. I don’t do that kind of thing.
However, a Twitter check revealed that Tony Bain is familiar with Groovy Corp and the Groovy SQL Switch (apparently they started out in Australia, where he lives and works, and he evidently knows the guys). Tony’s take, in summary, is (emphasis mine):
- They are an in memory RDBMS
- They have worked with Intel to architect from the ground up for large multi processor concurrency
- Initially they are launching as a multi-core appliance
- They claim 200,000 sql operations per second from a single box
- They are proprietary (not built on MySQL or any other open source database) which means they have had a lot of control around their architecture
- They are a pretty cool company with some interesting people
There’s a little more detail at the above link.