Relational DBMS used to be fairly straightforward product suites, which boiled down to:
- A big SQL interpreter.
- A bunch of administrative and operational tools.
- Some very optional add-ons, often including an application development tool.
Now, however, most RDBMS are sold as part of something bigger.
- Oracle has hugely thickened its stack, as part of an Innovator’s Solution strategy — hardware, middleware, applications, business intelligence, and more.
- IBM has moved aggressively to a bundled “appliance” strategy. Even before that, IBM DB2 long sold much better to committed IBM accounts than as a software-only offering.
- Microsoft SQL Server is part of a stack, starting with the Windows operating system.
- Sybase was an exception to this rule, with thin(ner) stacks for both Adaptive Server Enterprise and Sybase IQ. But Sybase is now owned by SAP, and increasingly integrated as a business with …
- … SAP HANA, which is closely associated with SAP’s applications.
- Teradata has always been a hardware/software vendor. The most successful of its analytic DBMS rivals, in some order, are:
- Netezza, a pure appliance vendor, now part of IBM.
- Greenplum, an appliance-mainly vendor for most (not all) of its existence, and in particular now as a part of EMC Pivotal.
- Vertica, more of a software-only vendor than the others, but now owned by and increasingly mainstreamed into hardware vendor HP.
- MySQL’s glory years were as part of the “LAMP” stack.
- Various thin-stack RDBMS that once were or could have been important market players … aren’t. Examples include Progress OpenEdge, IBM Informix, and the various strays adopted by Actian.
This phenomenon is, I think, much more driven by vendors than users. Most of the examples I listed work or could work perfectly well on their own.* But relational database management systems are seen as “strategic” products, which means in particular:
- They’re often expensive to adopt (software, hardware, people costs).
- They’re also often expensive to switch away from.
And strategic products, high price tags, and thick product stacks commonly go together.
*Netezza is an exception. But Exadata is not; while Oracle data warehousing was in a bad technical place before Exadata, Exadata software is what cleaned the problem up.
Also relevant is that I took those examples from relatively mature RDBMS market segments — high-end OLTP/general purpose (OnLine Transaction processing), mid-range OLTP/general-purpose, and analytic. Products in those sectors have had enough time to be built out. They also tend to have fairly close competitors, as the most important product features (e.g. columnar storage in analytic RDBMS, or online backup across the board) have been imitated numerous times each.
NewSQL, by way of contrast, is just as thin-stack as NoSQL is. Products in those sectors are immature; vendors are completing them first before wedding them to other technology layers. They’re also strongly differentiated; if you tell me what topology you need and which style(s) of API or DML (Data Manipulation Language) you prefer, the list of product candidates I give you may be short indeed.
HBase is the obvious exception to my “NoSQL products stand alone” generalization, but its market position is a matter of debate.
I have mixed feelings about this trend. For starters, I’m grudgingly becoming more sympathetic to DBMS/hardware bundles, notwithstanding their role as a way to gouge more money from customers than the hardware is actually worth. Why? Because of my opinion that there’s a general move toward appliances, clusters and clouds. In particular:
- As DBMS become better at straddling and melding RAM, flash and disk, legitimate reasons to optimize hardware/software integration will increase.
- Microsoft (with Parallel Data Warehouse) and SAP (with HANA) induce customers to adopt hardware “appliances” even though they don’t sell and profit from the hardware themselves. This shoots down the argument that appliances are only a vendor trick to squeeze out more profits.
- Netezza’s super-easy installation was a really nice feature.
When it comes to RDBMS/business intelligence bundles, my thoughts start:
- As a general rule, a benefit of BI is that it can get at data from lots of different sources. This speaks against tying it to a specific DBMS.
- The vendor-specific evidence is mixed:
- IBM has never explained any user advantages to including Cognos in its analytic “appliance” product lines.
- Teradata did some special optimizations for MicroStrategy. This suggests that, conversely, MicroStrategy could benefit from DBMS-specific features.
- QlikView built a custom in-memory data store.
- Specialized business intelligence stacks are on the rise, although generally with a beyond-just-relational flavor.
And so I’m skeptical about RDBMS/BI integration, but willing to be persuaded otherwise.
The integration of advanced analytics with RDBMS leaves me perplexed. Gains in performance, scalability and/or development ease would seem, in many cases, too great to pass up. (E.g.. the Teradata Aster 6 story, analytic libraries and all.) And indeed most analytic platform vendors report some level of adoption. But the whole thing is moving more slowly than I expected. Meanwhile in the Hadoop world, a much lesser SQL capability — Hive — seems to be integrated into other analytic processing with enthusiasm. Perhaps the problem is that enterprises have to figure out which analytic techniques to use in the first place, before they worry too much about making them efficient.
And finally, when it comes to bundling of packaged applications with RDBMS — that depends on the class of application.
- At the high end, it’s almost purely a pricing ploy, as those apps are usually written for lowest-common-denominator SQL functionality, so as to preserve portability.
- A lot of mid-range apps are written against a specific DBMS, which is then resold along with the app. What’s more …
- … most of those apps will migrate over time to a SaaS (Software as a Service) delivery model, which allows for a wholly integrated stack. And as the Workday example teaches us, database choices for SaaS apps can be pretty imaginative.
- The refactoring of everything (July, 2013)
- Comments about Gartner’s comments about a bunch of DBMS products (November, 2013)
- The cardinal rules of DBMS development (March, 2013)