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DRL (Drools Rule Language) is Drools’ native, text-based language for authoring business rules. Each rule follows a simple when / then shape: a when block describes the conditions to match against the facts in working memory, and a then block describes the actions to take when those conditions hold. Because it is written as code rather than diagrams, DRL is more expressive and powerful than DMN for complex inference — chaining rules, reasoning over large fact sets, and fine-grained control — at the cost of being Drools-specific rather than a portable standard.
DRL example showing a when/then rule that flags a high-risk loan applicant

A simple DRL rule: when an applicant's credit score is below 600, flag them as high risk and require review.

The engine evaluates DRL rules with a high-performance pattern-matching algorithm (Rete), so you declare what should happen and the engine decides when each rule fires.

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Where to go next

DMN, DRL, BPMN

How DRL compares to DMN and BPMN, and when to use each.

DRL

How DRL fits into decision automation in the Aletyx architecture.

Syntax Basics

The fundamentals of DRL syntax and rule structure.

Conditions (LHS)

How the when block matches facts in working memory.

Actions (RHS)

How the then block defines what happens when a rule fires.

DRL Examples

Worked DRL rule examples you can learn from and adapt.