RAM is the hip place to be. For modern applications built to scale out to thousands or even millions of users, scaling the data behind those applications has long been a difficult task. But a host of in-memory data grids from companies like McObject, Oracle and Terracotta are solving the scalable data-store problem, and they all expect 2013 to be a banner year for such software.
Massimo Pezzini, vice president and fellow at Gartner Research, said he expects explosive growth in the in-memory data store market in 2013. While the research he cited is not yet published, he did have figures on the market and its potential for growth.
“We think in 2011 the market for in-memory database was approximately US$250 million in terms of license and maintenance revenue… We’ve spoken with vendors, and some are projecting high double-digit, if not triple-digit growth in 2013. Terracotta is expecting to triple its revenues this year. We think this is going to be a $1 billion market by 2016. In software, $1 billion is a big market,” he said.
There are many reasons for this growth, but Pezzini said a few use cases are most common. “I would say the most obvious use case is really caching: caching a database, caching a session in a website, etc.,” he said. “Quite a lot of customers have started using an in-memory data grid in that way: their own layer to speed up the performance of Web applications.” But new use cases are cropping up thanks to the proliferation of clouds and the need to operate at scale.
“Lately, we have seen examples of customers using an in-memory data grid as a data-management platform, as a platform to host the database of record,” said Pezzini. “In business practice, that is not relational, because in-memory data grids are based on an object-oriented NoSQL paradigm. This is one of the reasons customers are looking into in-memory data grids.”
Mike Allen, vice president of product management at Terracotta, thinks there are a few reasons behind the growth of in-memory data grids, but there’s one large factor he cited. “One is data volume, and now you can suddenly get machines with a lot of memory very cheaply,” he said. “You can stack up six servers with a half-terabyte of RAM each, and then keep all your data in memory, which was never really possible before. We scale that grid predictably and scale it to that capacity.”