By Freya Purnell
IBM PureData, SAP HANA, Teradata Aster Discovery Platform and HP Vertica have been named by analyst firm Ovum as leaders in the analytic database solutions market.
But there’s no room for complacency – challengers Kognitio, SAP Sybase IQ and ParAccel are nipping at their heels and could break into the leader category within the next year.
The emergence of purpose built and workload-optimised analytic databases over the past few years has given the previously commoditised database market a shake-up.
According to Ovum’s latest ‘Decision Matrix: Selecting an Analytic Database, 2013-14’, an increasing number of organisations are now revisiting their current analytics strategies and are looking to implement specialised analytic databases that promise to keep pace by delivering more advanced analytics in bigger and faster data environments.
“The business case of purchasing and implementing an analytic database is becoming clearer. Traditional data warehousing architectures are struggling to manage larger data volumes, handle new type of human and machine generated data, deliver rapid query response and devise more sophisticated analytics,” said Surya Mukherjee, senior analyst at Ovum.
In response to these needs, vendors have incorporated certain core design principles in the software and hardware to improve performance, including conventional query optimisation, smart index management, pre-calculated views, in-memory processing and columnar storage for software, and MPP architectures, in-memory engines and pre-configured appliances in the hardware space.
Support for in-memory processing is a common theme, but the level to which solutions use in-memory varies widely.
“An ideal – for performance purposes – would of course be to put all data into memory. However, despite the falling cost-versus-performance [equation], it is still more expensive than partial disk and memory platforms, and the cost-versus-performance differential influences enterprises’ selection processes,” Mukherjee said.
All the databases covered in the report provide strong support for advanced analytics, either in-database, through UDFs (user-defined functions), or by supporting parallelized versions of R open source statistical software, but Ovum warns enterprises to examine carefully the predictive libraries of shortlisted vendors.
“A point to note in our research is that all the vendors who participated, support fast deployment of cloud and appliances. The approaches to cloud and appliances do vary, with some such solutions available only on pre-configured appliances or private clouds, while others are available as commodity hardware. Cloud deployment will undoubtedly be a key area of development for all database vendors in the medium term,” said Mukherjee.
