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Create a plugin for rule engines, such that a Business rule engine can use JavaSpace as the working memory for the rule engine. More specifically, I am thinking of BRE that implement RETE algorithm and use assert/retract semantics. by combining a data grid with a rule engine, you get a compute grid.

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Create a plugin for rule engines, such that a Business rule engine can use JavaSpace as the working memory for the rule engine. More specifically, I am thinking of BRE that implement RETE algorithm and use assert/retract semantics. by combining a data grid with a rule engine, you get a compute grid.

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For many business applications like financial systems, the government requires each transaction go through validation. A common example is a "hit list" of known criminals or compromised accounts. Other processes like fraud detection would benefit from the combination of a data grid with a compute grid. By combining the two, each node can perform complex logic and queries and send the aggregated result to the client application.

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For many business applications like financial systems, the government requires each transaction go through validation. A common example is a "hit list" of known criminals or compromised accounts. Other processes like fraud detection would benefit from the combination of a data grid with a compute grid. By combining the two, each node can perform complex logic and queries and send the aggregated result to the client application.

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Coherence currently supports work managers that can perform distributed queries across the cluster. This approach differs in several ways. The first is that coherence only supports simple queries and does not support complex logic. The second is that using a rule engine provides greater expressiveness. Developers can use functional and declarative programming techniques to define rules that will reason over the data in the data grid. The third benefit is a rule engine implementing RETE algorithm will produce optimal query plan, which reduces the execution cost and improves the performance.

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Coherence currently supports work managers that can perform distributed queries across the cluster. This approach differs in several ways. The first is that coherence only supports simple queries and does not support complex logic. The second is that using a rule engine provides greater expressiveness. Developers can use functional and declarative programming techniques to define rules that will reason over the data in the data grid. The third benefit is a rule engine implementing RETE algorithm will produce optimal query plan, which reduces the execution cost and improves the performance.