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First, I transformed this Trie Tree implementation into an open-source project, which I called Praecepta (Rules in Latin), so anyone can try it out. Then, I added three modules to it, with a decision table based on a real scenario (blurred input/output values). Each module uses a different framework: Praecepta, Camunda 7, and Kogito (the newest Kie solution for the Cloud).
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CodeRabbit
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kogito-runtimes
This repository is a fork of apache/incubator-kie-kogito-runtimes. Please use upstream repository for development.
First, I transformed this Trie Tree implementation into an open-source project, which I called Praecepta (Rules in Latin), so anyone can try it out. Then, I added three modules to it, with a decision table based on a real scenario (blurred input/output values). Each module uses a different framework: Praecepta, Camunda 7, and Kogito (the newest Kie solution for the Cloud).
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I used SpringBoot 3.0.2, GraalVM 22 (JVM mode), a MacOS 2,6 GHz 6-Core Intel Core i7, running 1000 users for 5 minutes. The idea was to test how memory consumption and CPU usage evolve. Below, I compared the footprint of these three solutions. I collected the total count of requests, throughput, memory consumption, and CPU usage using VisualVM and Gatling.
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Camunda BPM
C7 CE enters EOL in October 2025. Please check out C8 https://github.com/camunda/camunda – Flexible framework for workflow and decision automation with BPMN and DMN. Integration with Quarkus, Spring, Spring Boot, CDI.
In Pictet Technologies, my team relies a lot on decision models. These models allow our business analysts to input Compliance business rules directly into the systems with minimal developer intervention. When I joined the company, we used to use both Drools and Camunda. However, we faced severe memory and performance issues, specifically with Camunda, prompting me to explore alternatives.