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
How Hyperion will change Oracle
Oracle is evidently buying Hyperion Software. Much like Gaul, Hyperion can be divided into three parts:
- Budgeting and consolidation applications, descended from the original Hyperion and Pillar.
- Essbase, the definitive MOLAP engine, descended from Arbor Software.
- A business intelligence suite, descended from Brio.
The most important part is budgeting/planning, because it could help Oracle change the rules for application software. But Essbase could be just the nudge Oracle needs to finally renounce its one-server-fits-all dogma.
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| Categories: Analytic technologies, Data warehousing, Microsoft and SQL*Server, MOLAP, Oracle | 17 Comments |
Opportunities for disruption in the OLTP database management market (deck-clearing post #2)
The standard Clayton Christensen “Innovator’s Dilemma” disruption narrative goes something like this:
- Market leaders have many advantages, including top technology.
- Followers come up with good technology too.
- The leaders stay ahead by making their products ever better and more complex.
- The followers sell into new or non-mainstream markets, at prices the leaders can’t match. So they dominate new markets.
- Old markets turn into low-margin commodity-fests.
- Old leaders are screwed.
And it’s really hard for market leaders to avert this sad fate, because the short- and intermediate-term margin hit would be too great.
I think the OLTP DBMS market is ripe for that kind of disruption – riper than commentators generally realize. Here are some key potential drivers:
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OLTP database management system market – the consensus isn’t ALL wrong (deck-clearing post #1)
Most of what I’ve written lately about database management seems to have been focused on analytic technologies. But I have a lot to say on the OLTP (OnLine Transaction Processing) side too. So let’s start by clearing the decks. Here’s a list of some consensus views that I in essence agree with:
- Oracle is the top of the line, and has nothing wrong with it other than cost of ownership and the non-joys of doing business with Oracle Corporation.
- DB2/mainframe is a fine product, but only if you like IBM mainframes.
- DB2/open systems is another fine product, but it’s hard to think of reasons to use it over Oracle.
- Microsoft SQL Server has great cost of ownership if you’re a Windows (server) shop anyway, especially on the administrative side. It does most but not all of what Oracle does.
- Sybase Adaptive Server Enterprise is a lot like SQL Server, but without the Windows dependence or the great Microsoft tools. If you have it installed or are Chinese, you should strongly consider using it, but otherwise there are better alternatives.
- Progress’ DBMS is great if you don’t need any of the features it’s missing. Administration, for example, is a super-low-cost breeze. But why use it unless you’re also using the Progress development tools?
- Intersystems’ Cache’ is another fine mid-range product that involves buying into the vendors’ whole tool set – all the more so because it isn’t relational.
- Small-footprint embedded DBMS, from vendors such as Sybase’s iAnywhere division or Solid Information Technologies, are off in their own little world. Mainly, that world is telecom, with a satellite in medical devices, although other kinds of networked equipment also sometimes use these products.
- IBM’s non-DB2 database management products – IMS, Informix, etc. – are fine things to stick with until you have to change. Ditto products from Software AG, Computer Associates, Cincom, etc.
- MySQL Version 4 is an OLTP joke, but it’s a joke many people share. (Hey — a lot of blogs, including mine, run on WordPress and MySQL 4.)
- Until Ingres is meaningfully marketed and sold outside its installed base, it’s not worth worrying about.
- PostgreSQL is more significant as the underpinning of other products — mainly EnterpriseDB in the OLTP space — than it is in its own right.
Really big databases
Business Intelligence Lowdown has a well-dugg post listing what it claims are the 10 largest databases in the world. The accuracy leaves much to be desired, as is illustrated by the fact that #10 on the list is only 20 terabytes, while entirely unmentioned is eBay’s 2-petabyte database (mentioned here, and also here). Read more
| Categories: Data warehouse appliances, Data warehousing, DATAllegro, Greenplum, IBM and DB2, Netezza, Oracle, SAS Institute, Teradata, Theory and architecture | 4 Comments |
EnterpriseDB’s Oracle clone — fact or fiction?
PostgreSQL-based EnterpriseDB is attracting a bit of attention. Philip Howard, as he does of most products, takes a favorable view. Seth Grimes regards the company as dirty, rotten liars. The company suggests that Everquest gameplay* runs on an RDBMS. I find this inherently implausible, and hence am starting out with a skeptical view of the company’s marketing messages.
*As in character movement. The idea that character inventory is stored in an RDBMS I find vastly more credible. Ditto other less volatile aspects of character state.
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| Categories: ANTs Software, Emulation, transparency, portability, EnterpriseDB and Postgres Plus, Games and virtual worlds, Mid-range, OLTP, Open source, Oracle, PostgreSQL | 4 Comments |
Data mining is driving much of data warehousing
Until I did all this recent research on data warehousing, I didn’t realize just how big a role data mining plays in driving the whole thing. Basically, there are three things you can do with a data warehouse – classical BI, “operational” BI, and data mining. If we’re talking about long-running queries, that’s not operational BI, and it’s not all of classical BI either. The rest is data mining. Indeed, if you think back to what you know of the customer bases at data warehouse appliance vendors Netezza and DATallegro, there are a lot of credit-reporting-data types of users – i.e., data miners. And it’s hard to talk about uses for those appliances very long without SAS extracts and the like coming up.
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| Categories: Data warehouse appliances, Data warehousing, DATAllegro, Netezza, Oracle, Predictive modeling and advanced analytics | 8 Comments |
Vendor segmentation for data warehouse DBMS
February, 2011 edit: I’ve now commented on Gartner’s 2010 Data Warehouse Database Management System Magic Quadrant as well.
Several vendors are offering links to Gartner’s new Magic Quadrant report on data warehouse DBMS. (Edit: This is now a much better link to the 2006 MQ.) Somewhat atypically for Gartner, there’s a strict hierarchy among most of the vendors, with Teradata > IBM > Oracle > Microsoft > Sybase > Kognitio > MySQL > Sand, in each case on both axes of the matrix. The only two exceptions are Netezza and DATallegro, which are depicted as outvisioning Microsoft somewhat even as they trail both Microsoft and Sybase in execution.
Gartner Magic Quadrants tend to annoy me, and I’m not going to critique the rankings in detail. But I do think this particular MQ is helpful in framing a vendor segmentation, namely:
- Big full-spectrum MPP/shared-nothing vendors: Teradata and IBM.
- MPP/shared-nothing appliance upstarts: Netezza and DATallegro
- Big SMP/shared-everything vendors who also are apt to be your OLTP incumbent, and who want to integrate your software stack soup-to-nuts: Oracle and Microsoft
- Niche vendors: Pretty much everybody else
| Categories: Data warehouse appliances, Data warehousing, DATAllegro, IBM and DB2, Microsoft and SQL*Server, Netezza, Oracle, Parallelization, Teradata | 6 Comments |
Relational data warehouse Expansion (or Explosion) Ratios
One of the least understood aspects of data warehouse technology is what may be called the
Expansion Ratio = (Total disk space used, except for mirroring) / (Size of the base database).
This is similar to the explosion ratio discussed in the OLAP Report’s justly famous discussion of database explosion, but I’m going with my own terminology because I don’t want to be tied to their precise terminology, nor to their technical focus. Expansion Ratios are hotly debated, with some figures being:
- Teradata claims an Expansion Ratio of 8-9X for Oracle, 6X for DB2 (open system version), and 2.5X for Teradata. The underlying source is data warehouses they’ve replaced, so there may be a bias toward out-of-control warehouses on the part of their competitors.
- An anonymous appliance vendor exec said to me off the top of his head that Oracle has 6-8X Expansion Ratios.
- Oracle’s TPC-H submissions in the largest size range (10 terabytes) have 9.7-10.5X Expansion Ratios, if I’m reading the TPCs correctly.
- Oracle cites a survey of 8 customers with 10-60 Tb database size in which the Expansion Ratio works out to 1.6X. (More on this anomalous result below.)
I don’t have actual figures from Netezza and DATallegro, but I imagine they’d come out lower than 2X, possibly well below.
| Categories: Data warehouse appliances, Data warehousing, Database compression, DATAllegro, IBM and DB2, Netezza, Oracle, Teradata | 9 Comments |
Oracle and Microsoft in data warehousing
Most of my recent data warehouse engine research has been with the specialists. But over the past couple of days I caught up with Oracle and Microsoft (IBM is scheduled for Friday). In at least three ways, it makes sense to lump those vendors together, and contrast them with the newer data warehouse appliance startups:
- Shared-everything architecture
- End-to-end solution story
- OLTP industrial-strengthness carried over to data warehousing
In other ways, of course, their positions are greatly different. Oracle may have a full order-of-magnitude lead on Microsoft in warehouse sizes, for example, and has a broad range of advanced features that Microsoft either hasn’t matched yet, or else just released in SQL Server 2005. Microsoft was earlier in pushing DBA ease as a major product design emphasis, although Oracle has played vigorous catch-up in Oracle10g.
| Categories: Data warehouse appliances, DATAllegro, EAI, EII, ETL, ELT, ETLT, IBM and DB2, Microsoft and SQL*Server, Netezza, Oracle, Parallelization, Teradata | 1 Comment |
Competitive issues in data warehouse ease of administration
The last person I spoke with at the Netezza conference on Tuesday was a customer/presenter that the company had picked out for me. One thing he said baffled me — he claimed that Netezza was a real appliance vendor, but DATallegro wasn’t, presumably due to administrability issues. Now, it wasn’t clear to me that he’d ever evaluated DATallegro, so I didn’t take this too seriously, but still the exchange brought into focus the great differences between data warehouse products in the area of administration. For example:
- Netezza has no indices at all. And no caches. And the hardware is preconfigured. This all makes administration pretty simple.
- DATallegro has almost no indices, and also has preconfigured hardware. But it has some partitioning, optionally.
- Teradata also has preconfigured hardware. It does have indices, but rather simple ones. Plus it has join indices. And it has a few more configuration options in other areas (e.g., block size) than the other appliance vendors. (Yes, I count Teradata among the appliances.)
- If you go through all the fuss of installing SAP’s applications and BI technology anyway, the incremental administration of just SAP BI Accelerator is pretty light.
- Oracle and IBM have mammothly complex indexing options, but have put large amounts of work into tools to lessen the resulting administrative burden.
- IBM offers preconfigured hardware units to simplify some installation issues.
- Come to think of it, I don’t really know how hard it is to administer columnar systems (e.g., Sybase IQ).
| Categories: Data warehouse appliances, Data warehousing, DATAllegro, Greenplum, IBM and DB2, Netezza, Oracle, SAP AG, Teradata | 3 Comments |