GemStone Systems announced a 30-day evaluation program for GemFire Real-Time Events (RTE). Developed in collaboration with leading financial services firms, GemFire RTE is a distributed main-memory event processing and analytics solution based on continuous querying. Unlike a traditional relational database where applications execute queries on static data, GemFire RTE enables Java/J2EE applications to continuously process and analyze complex events, delivering a real-time view of critical data without the need to re-execute queries. C++ and C# applications can also plug into GemFire RTE via a standard adapter provided by GemStone.

GemFire RTE provides an in-memory relational data store that allows clients to register SQL-92 queries via JDBC. With any event/data update, RTE automatically evaluates queries that have been impacted, quickly regenerates a new view for those queries and proactively delivers updated result-sets or "row deltas" to distributed client applications. As deltas are pushed from RTE to client applications, RTE invokes client API callbacks with the set of Row Deltas as arguments, enabling users to build code that handles exact deltas to the JDBC results set. The Continuous Query (CQ) functionality allows users to obtain new, updated results from the in-memory database without having to issue the same query repeatedly. RTE offers a simple and intuitive client-programming model involving a JDBC compatible driver along with a simple extension to receive "delta" events on cached result sets from servers.

GemFire RTE's continuous querying technology works through an engine that efficiently groups and filters predicates from large numbers of queries, enabling the following to occur:

• When the server first receives a continuous query, it not only replies with an initial result set, but it analyzes the query predicates (selection criteria) in order to logically group it with other similar queries.

• The engine can then quickly identify what continuous queries are affected by any given data modification (an insert, update, or delete against the relationally structured operational data).

• The engine can send only the delta's to each CQ client needed to update its existing result set, in effect exactly the data necessary for the client to hold a materialized view of data from the server.

"Simultaneous dynamic updates and queries quickly inundate and freeze standard relational database technology," said Jags Ramnarayan, chief architect at GemStone Systems. "GemFire RTE with Continuous Querying ensures analysis of large volumes of real-time data, enabling firms to efficiently and continuously manage complex state changes. The advanced continuous query technology maximizes dynamic data environments, significantly reducing data latency to improve the speed and agility of critical business applications."

RTE eliminates the need to poll databases to refresh result sets, enabling users to build scalable system architectures previously unavailable with standard disk-based or in-memory relational databases. A single HA-pair of RTE servers simultaneously handle thousands of database updates per second while servicing hundreds or thousands of affected client continuous queries, ensuring consistent application performance. RTE is suitable both for building new database applications with high-performance query requirements and retrofitting existing client/server implementations that have reached their scalability limits. Developed and tested to the highest enterprise standards, RTE is designed for non-stop business critical operations, providing robust scalability, high-availability and failover features.