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Are there any implementations of production rule systems that operate out of core?
I've checked out the open source implementations like CLIPS and Jess, but these only operate in memory, so they tend to crash or force heavy disk swapping when operating on large numbers of facts and rules (e.g. in the billions/trillions).
I'm playing around with the idea of possibly porting a simple rules engine, like Pychinko to a SQL backend, using Django's ORM. However, supporting the level of functionality found in CLIPS would be very non-trivial, and I don't want to reinvent the wheel.
Are there any alternatives for scaling up a production rule system?
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A rules engine is all about providing an alternative computational model. Instead of the usual imperative model, which consists of commands in sequence with conditionals and loops, a rules engine is based on a Production Rule System.
RulesEngine is a highly extensible library to build rule based system using C# expressions. Features. Json based rules definition. Multiple input support. Dynamic object input support.
For software developers, a rule engine is useful only if it liberates them from expressing the rule in the code. In order to avoid this pitfall, it is commonly accepted that we should use rule engines only if appropriate, or not use them at all. Over the past decades, that has become a self-fulfilling prophecy.
you can check JENA and similar RDF rule engines which are designed to work with very large fact databases.
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