In the rushing torrent of computer science, a few concepts stand like rocks which resist being swept away. One of the most familiar and useful is relational database technology. It took a relatively short time for this concept to be identified (in Codd's paper of 1970) and implemented commercially (around 1975, in IBM's System R, among others). Perhaps only 10 or 15 years elapsed between the earliest database systems and the emergence of commercially viable RDBMS . For over 30 years since then RDBMS's have stood the test of time and repelled all challengers to their central role in data management.
A recent and serious challenger was Object database technology. In the 1990's this area looked poised to ride the gathering wave of object-oriented programming and sweep aside the fusty old RDBMS technology. Since then, while the OO wave has swept far up the beach, the promise of ODBMS seems to have been left behind in the receding foam, never having been fully realized.
So why is this?
I think one reason is that the relational paradigm could be a fundamental data structure for information representation. In a sense, relations are the machine code of data modelling - they can be used to represent any required data model. Granted, relational models aren't alway elegant or efficient - but that simply confirms the metaphor. Moreover, their simplicity allows relational theory to be firmly grounded in mathematics and logic. (Of course, the relational hard-cores have been saying this for years - in some cases a bit too vociferously, IMHO. I'm just reluctantly coming round to think that they might be right.)
A further piece of evidence for this observation is that RDBMS vendors have a fine track record of being able to adapt the core paradigm to accomodate new technical ideas. Queuing, security models, data analytics, and of course even (to an extent) object-orientation are some of the areas which have been implemented quite reasonably in terms of an underlying relational model.
ODBMS's, in contrast, have never quite seemed to develop a truly compelling and general paradigm. The various OO query languages don't seem to have the expressive power of SQL, and Object data models seem to run up against thorny semantic issues sooner than relational ones do (such as schema evolution and inheritance modelling). Granted, implementing an object-based data model using relational technology doesn't actually solve any of these issues, but somehow the maturity of relational techniques and tools make them seem less painful.
Some people (myself included) have tended to see the rise of Object-Relational mapping technology as at best a temporary expedient, and at worst a string-and-baling-wire solution to cope with the OO-RDB impedance mismatch. Just give ODB's a few more years to mature, we hope, and we can do away with this inelegant hack! But if relational really is a fundamental concept, perhaps the quest for pure OO databases is misguided. Perhaps O-R mapping tools are the final goal, not just a stop-gap. They can be thought of as compilers for the data access layer (with all the opportunity for performance improvement and platform independence that the compilation paradigm provides).
This isn't to say that RDB technology has evolved as far as it needs to. I hope to see much more powerful querying capability, using concepts from the areas of logic and functional programming, machine reasoning and knowledge representation. All of these seem to be continuing to mature - I look forward to seeing them make the leap to practicality like OO did years ago.
The Rise of Test Impact Analysis
1 week ago