Oracle
Analysis of software titan Oracle and its efforts in database management, analytics, and middleware. Related subjects include:
- Oracle TimesTen
- (in The Monash Report)Operational and strategic issues for Oracle
- (in Software Memories) Historical notes on Oracle
- Most of what’s written about in this blog
SolidDB caching for DB2
It’s just at the proof-of-concept stage, but Solid has a nice write-up about SolidDB being used as a front-end cache for DB2. Well, it’s a marketing document, so of course there’s a lot of pabulum too, but interspersed there’s some real meat as well. Highlights include 40X throughput improvement and 1 millisecond average response time (something that clearly can’t be achieved with disk-centric technology alone).
Analogies to Oracle/TimesTen are probably not coincidental; this is exactly the upside scenario for the TimesTen acquisition, as well as being TimesTen’s biggest growth area towards the end of its stint as an independent company.
Categories: Cache, IBM and DB2, Memory-centric data management, OLTP, Oracle, Oracle TimesTen, solidDB | 1 Comment |
More on stream processing integration with disk-based DBMS
Mike Stonebraker wrote in with one “nit pick” about yesterday’s blog. I had credited Truviso for strong DBMS/stream processor integration. He shot back that StreamBase has Sleepycat integrated in-process. He further pointed out that a Sleepycat record lookup takes only 5 microseconds if the data is in cache. Assuming what he means is that it’s in Sleepycat’s cache, that would be tight integration indeed.
I wonder whether StreamBase will indefinitely rely on Sleepycat, which is of course now an Oracle product …
Categories: Memory-centric data management, Michael Stonebraker, Oracle, StreamBase, Streaming and complex event processing (CEP) | Leave a Comment |
RDF “definitely has legs”
Thus spake Mike Stonebraker to me, on a call we’d scheduled to talk about several other things altogether. This was one day after I was told at the Text Analytics Summit that the US government is going nuts for RDF. And I continue to get confirmation of something I first noted last year — Oracle is pushing RDF heavily, especially in the life sciences market.
Evidently, the RDF data model is for real … unless, of course, you’re the kind of purist who cares to dispute whether RDF is a true “data model” at all.
Categories: Data models and architecture, Oracle, RDF and graphs, Theory and architecture | Comments Off on RDF “definitely has legs” |
Naming the DBMS disruptors
Edit: This post has largely been superseded by this more recent one defining mid-range relational DBMS.
I find myself defining a new product category – midrange OLTP/multipurpose DBMS. (Or just midrange DBMS for brevity.) Nothing earthshaking here; I’m simply referring to those products that: Read more
Deal prospects for data warehouse DBMS vendors
The fourth Monash Letter is now posted for Monash Advantage members (just 3 pages this time). It’s about forthcoming M&A in data warehouse DBMS, something that seems likely just because of the large number of current players. Some of the observations are:
- Oracle needs to buy somebody, because of its rather dire product problems at the data warehouse high end. And it’s very much in keeping with their recent behavior to do so.
- Teradata could be acquired sooner than people think. While there are tax considerations preventing an outright sale, these should be obviated if all of the current NCR is taken private. What’s more NCR minus Teradata is exactly the kind of healthy, slow-growth, niche company that private equity loves.
- DATAllegro is a natural merger partner for somebody. Their technical differentiation is almost DBMS-independent, so it could be easy to roll them into a larger overall product strategy. And they have enough market traction to have proved some non-trivial value.
- Kognitio seems desperate these days, with several odd or even underhanded marketing tactics. But they do have MPP bitmap software, something Sybase sorely lacks. So there’s an obvious potential combination between those two.
Categories: Data warehouse appliances, Data warehousing, DATAllegro, Kognitio, Oracle, Sybase, Teradata | 3 Comments |
Oracle/Google/Apple merger – wow! Just — wow.
If rumors are to be believed, Oracle, Google, and Apple are close to agreeing on a mega-blockbuster three-way merger. Just the personality combinations are amazing, starting with close friends Jobs and Ellison — perhaps the two greatest entrepreneurs of Silicon Valley, and both with impeccable taste – and the traditionally sloppy, generation-younger Page and Brin. But let’s jump straight to some of the possible business and technology ramifications.
The Macintosh could become a serious Windows competitor. The Mac is quietly making an enterprise comeback anyway. Business intelligence, dashboards, and the like are constantly in the throes of UI re-invention. (I have some articles I the works about why the industry never seem to get them right, but in the mean time here is my UI overview article from last year.)
Whole new generations of personal/pervasive computing devices could evolve. Apple obviously is a huge personal-electronic-device player with the iPod and upcoming iPhone. Google has looked into cell phones as well. Designing cool devices will not be a problem. The issue is making them integrate really well with enterprise systems. I favor speech interfaces, myself.
Enterprise information management could be transformed. Oracle is batting about 0-for-the-decade in search. Google has is selling a lot of not-terribly-useful low-end enterprise search boxes. There’s room for both to do a lot better. Ex-Oracle executive Dennis Moore has some good ideas in that regard.
Related link
- Scoble has details on part of the story.
There’s one catch, however: On April 1, rumors generally should not be taken too seriously.
Categories: Google, Oracle | 2 Comments |
Oracle, Tangosol, objects, caching, and disruption
Oracle made a slick move in picking up Tangosol, a leader in object/data caching for all sorts of major OLTP apps. They do financial trading, telecom operations, big web sites (Fedex, Geico), and other good stuff. This is a reminder that the list of important memory-centric data handling technologies is getting fairly long, including:
- Object caching (e.g., Tangosol, Progress ObjectStore)
- In-memory RDBMS (e.g., Oracle TimesTen, Solid BoostEngine, McObject eXtremeDB)
- Stream processing (e.g., Progress Apama, Streambase)
And that’s just for OLTP; there’s a whole other set of memory-centric technologies for analytics as well.
When one connects the dots, I think three major points jump out:
- There’s a lot more to high-end OLTP than relational database management.
- Oracle is determined to be the leader in as many of those areas as possible.
- This all fits the market disruption narrative.
I write about Point #1 all the time. So this time around let me expand a little more on #2 and #3.
Read more
EnterpriseDB tries PostgreSQL-based Oracle plug-compatibility
Like Greenplum, EnterpriseDB is a PostgreSQL-based DBMS vendor with an interesting story, whose technical merits I don’t yet know enough to judge. In particular, CEO Andy Astor:
- Confirms that EnterpriseDB is OLTP-focused, unlike Greenplum. That said, they are also used for some reporting and so on. But they don’t run 10s-of-terabytes sized data marts.
- Claims EnterpriseDB has a high level of Oracle compatibility – SQL, datatypes, stored procedures (so that would be PL/SQL too), packages, functions, etc.
- Claims ANTs isn’t nearly as Oracle-compatible.
- Claims 50-100% better OLTP performance out of the box than vanilla PostgreSQL, due to auto-tuning.
Also, EnterpriseDB has added a bunch of tools to PostgreSQL – debugging, DBA, etc. And it provides actual-company customer support, something that seems desirable when using a DBMS. It should also be noted that the product is definitely closed-source, notwithstanding EnterpriseDB’s open-source-like business model and its close ties to the open source community.
Read more
Categories: Actian and Ingres, ANTs Software, Data warehousing, Emulation, transparency, portability, EnterpriseDB and Postgres Plus, Mid-range, OLTP, Open source, Oracle, PostgreSQL | 2 Comments |
DBMS market competitive overview (Part 1)
Monash Advantage members just received an exclusive nine-page Monash Letter with a competitive overview of the DBMS industry. The full analysis is exclusive to them, but I’ll give some highlights here.
1. As per my recent “deck-clearing” posts, there’s a lot more competitive opportunity in the DBMS industry than many observers recognize.
2. One reason is the considerable number of separate niches in the DBMS space.
3. Oracle is a classical Geoffrey Moore “gorilla” only in the market for high-end OLTP and mixed-used DBMS. Everything else is up for grabs.
4. As discussed here extensively, simpler appliance-like architectures are beating the overly complex general-purpose DBMS vendors’ solutions for VLDB data warehousing.
5. MPP/shared-nothing architectures are deservedly beating SMP/shared-everything approaches for VLDB data warehousing.
That’s not the only Monash Letter recently released; another one covered online marketing strategy and tactics.
Categories: Data warehouse appliances, Data warehousing, Database diversity, Oracle, Theory and architecture | Leave a Comment |
Why Oracle and Microsoft will lose in VLDB data warehousing
I haven’t been as clear as I could have been in explaining why I think MPP/shared-nothing beats SMP/shared-everything. The answer is in a short white paper, currently bottlenecked at the sponsor’s end of the process. Here’s an excerpt from the latest draft:
There are two ways to make more powerful computers:
1. Use more powerful parts – processors, disk drives, etc.
2. Just use more parts of the same power.
Of the two, the more-parts strategy much more cost-effective. Smaller* parts are much more economical, since the bigger the part, the harder and more costly it is to avoid defects, in manufacturing and initial design alike. Consequently, all high-end computers rely on some kind of parallel processing.
*As measured in terms of capacity, transistor count, etc., not physical size. Read more