Jim Groff, a senior vice president at Oracle and the former CEO of TimesTen Inc., says two broad trends are driving the migration of in-memory databases from niche markets, such as securities trading, into more mainstream computing. The first, on the hardware side, is the rise of inexpensive 64-bit microprocessor architectures that lift the old limit of 2GB of physical memory available to Wintel applications.
The second, in software, is "the emergence of an intelligent middle tier of the enterprise architecture," Groff says. In the middle tier, "where application servers live, where middleware lives, where business activity monitoring and Web services live, that's where there's a tremendous amount of action in enterprise IT today."
And all that action entails a lot of data queries and exchanges among application servers, database servers and storage networks. "The scaling can't keep up; the back end can't keep up," Groff says. "So intelligently caching the right information in the middle tier is emerging as a key solution." Cached information could include key customer data pulled forward into a customer call center at the beginning of a call so that common questions can be answered without delays, he explains.
Streaming technology will move into supply chain systems when radio- frequency identification tags go from the pallet level to the individual item level and a warehouse or store generates huge volumes of product-movement transactions, says Mike Stonebraker, founder and CTO of StreamBase Systems. "Long term, the huge market will be in the area of sensor networks. Everything on the planet of material significance may be tagged," he says.
"I definitely think these products deserve to be more in the mainstream," says Curt A. Monash, a Computerworld columnist and president of Monash Information Services, an IT consultancy in Acton, Mass. But, he adds, a lot depends on how vendors position them and how hard big vendors like Oracle push them.
Says Monash, "These are products you'd buy for a limited group of applications, and for those, they can be very valuable. But they are not general-purpose systems."
The following companies offer high-performance databases:
Name: Ants Software. URL: www.ants.com Product: Ants Data Server Claim to fame: SQL-compliant RDBMS resides in memory or on disk, or it spans both. Avoids most table-locking.
Name: Applix URL: www.applix.com Product: TM1 Claim to fame: Financial analysis/modeling in memory in Excel or Web client formats on data from back-end databases.
Name: Db4objects URL: www.db4o.com Product: db4o Claim to fame: Open-source object database for Java and .Net environments. No database administrator needed.
Name: GemStone Systems URL: www.gemstone.com Product: GemFire Enterprise Data Fabric Claim to fame: Data virtualization, distributed caching and complex event processing.
Name: Kx Systems URL: www.kx.com Product: kdb+ Claim to fame: Integrated RDBMS spans memory and disk for real-time streaming and back-end storage.
Name: Oracle URL: www.oracle.com Product: TimesTen In-Memory Claim to fame: In-memory RDBMS for embedded applications or front-end data caching.
Name: Progress Software URL: www.progress.com Product: ObjectStore ODBMS Claim to fame: Real-time object database management and modeling for Java and C++ environments.
Name: Skyler Technology URL: www.skylertech.com Product: Prime Processing Claim to fame: Real-time data-processing engine uses prime number theory for in-memory analytics for financial services.
Name: Solid Information Technology. URL: www.solidtech.com Products: EmbeddedEngine and BoostEngine Claim to fame: Integrated in-memory and on-disk RDBMSs.
Name: StreamBase Systems URL: www.streambase.com Product: StreamBase Claim to fame: High-volume, real-time, memory-resident data-stream processing engine.
Name: Vhayu Technologies URL: www.vhayu.com Product: Velocity Claim to fame: Analysis of real-time streaming and historical securities market data.