Mainstream database management system (DBMS) technology faces a challenge from new approaches that reject the relational model. The battleground is set to be the market for business intelligence based on very large databases.
Some main players in DBMS software are already jockeying for position with revamped database products aimed at recapturing ground lost to newer products. Recently Microsoft unveiled Kilimanjaro, the next massively scalable version of its SQL Server with a strong BI flavor, while database market number-one Oracle joined forces with Hewlett-Packard to launch its Exadata storage grid.
Both announcements shared a common theme: How to make huge volumes of data easily available to power business intelligence applications?
And the numbers in question are huge. We are, of course, familiar with "huge" numbers in time of billion-dollar banking-industry bail outs. But these figures are dwarfed by the numbers of transactions pouring into some company databases and the amount of storage needed to accommodate them.
Back in January, Google reckoned it processed 20 petabytes of data a day - a number that has doubtless grown significantly since. And even lower down the scale, LGR Telecommunications is reported to be adding 13 billion records each day to a 310 terabyte data warehouse system and expects its petabyte of disks to double in the next year.
Although such huge volumes are still relatively unusual, it will not be long before even relatively small organizations will think of terabytes and petabytes of data as commonplace. If they want to make practical use of the data in business intelligence applications, they will find their traditional relational DBMS technology stretched.
Cracks in the edifice
It is not only the logistics of storing and managing such enormous amounts of data that poses a big challenge to DBMS builders. There is also the problem of giving users access to the data in a form that it might actually be useful. User queries have grown more complex and the limitations of traditional access methods based on Structured Query Language (SQL) have been exposed.
The cracks in relational DBMS and the inadequacies of SQL were highlighted in a paper called The End of an Architectural Era, presented at the conference on Very Large Databases (VLDB) in September 2007. The collaborative work of several DBMS gurus - including Ingres/PostIngres originator Michael Stonebraker - the paper, declared the relational model obsolete and argued that alternative approaches were better suited to today's data management and access problems.