Oracle this week shipped an update to its Coherence in-memory data grid, a member of a class of middleware that some say may be on the cusp of broader adoption for cloud computing.
In-memory data grids store information that applications need in memory across a pool of servers, instead of reading it off disks, resulting in major performance gains.
The Coherence product is one of the more mature in a space occupied by offerings from IBM as well as smaller companies like GigaSpaces and a number of open-source projects. Microsoft is also developing a system dubbed "Velocity."
To date, such systems have breathed rarefied air, mostly supporting large-scale Web sites and high-throughput transactional systems, such as stock trading applications. The in-memory data grid market in total generated less than US$100 million in revenue during 2008, according to Gartner, which prefers the term "distributed caching platforms."
But some observers believe that in-memory approaches to data management could eventually gain serious traction in cloud-computing deployments.
"Current architectures, with a lot of elbow grease, have generally been good enough. But we are seeing a wide convergence on caching as [a] way to make slow disks perform," author Todd Hoff wrote in a March article on highscalability.com. "Truly enormous amounts of effort are going into adding cache and then trying to keep the database and applications all in-sync with cache as bottom-up and top-down driven changes flow through the system."
"After all that work, it's a simple step to wonder why that extra layer is needed when the data could have just as well be kept in memory from the start," Hoff added. "Now add the ease of cloud deployments and the ease of creating scalable, low-latency applications that are still easy to program, manage, and deploy. Building multiple complicated layers of application code just to make the disk happy will make less and less sense over time."
Other observers also see a natural role for products like Coherence in cloud computing.
The technologies would help applications that weren't originally designed for elastically scalable infrastructure systems like Amazon Web Services to run more effectively, albeit "via some re-engineering," Gartner analyst Massimo Pezzini said in a recent report.
None of this means in-memory data grids would completely supplant traditional relational databases, which would still be used for longer-term storage, audit trails and other needs, said Geva Perry, a former GigaSpaces executive who now consults and blogs on cloud-computing and enterprise software issues.
However, with the in-memory approach a relational database "becomes less critical, which in my opinion would threaten an Oracle," he said. "If it's less critical, [a customer] might be inclined to use cheaper [database] products."
This places traditional database companies like Oracle in a dilemma, but since the company is "so big and powerful, it's OK for them to play wait-and-see," Perry said.
Beyond vendor trepidation, other factors stand in the way of broader customer adoption, such as the complexity of deploying and managing the systems and limited support from systems integrators and ISVs, according to Pezzini.