4 Repos
Engines specialized in detecting temporal patterns and sequences within streams to trigger actions.
Distinct from Stream Processing Engines: Focuses on temporal pattern detection specifically, whereas Stream Processing Engines are general-purpose.
Explore 4 awesome GitHub repositories matching data & databases · Complex Event Processing Engines. Refine with filters or upvote what's useful.
Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite batch workloads. It functions as a stateful stream processor and a SQL stream processing engine, providing a unified runtime to execute relational queries and event-based transformations. The system is distinguished by its ability to manage persistent operator state to ensure exactly-once processing guarantees and consistency during failures. It features specialized capabilities for complex event processing to detect temporal patterns and handles out-of-order events using eve
Detects temporal patterns and sequences within data streams to trigger real-time actions.
This project is a business rules management system and rule engine designed to define, execute, and manage complex business logic decoupled from application source code. It provides a business logic compiler that transforms human-readable rule definitions into executable models for high-performance runtime evaluation. The system includes a complex event processing engine for analyzing real-time data streams to identify temporal patterns and a decision model and notation executor that processes structured logic based on industry standards for deterministic results. It utilizes an inference eng
Provides a specialized engine for detecting temporal patterns and sequences within real-time data streams to trigger actions.
Grule is a business rule engine for Go that decouples complex decision-making logic from core application code. It provides a framework for defining, versioning, and executing business rules through a domain-specific language, allowing logic to be managed independently of the underlying software implementation. The engine distinguishes itself by utilizing a formal grammar-based parser and a Rete-inspired pattern matching algorithm to evaluate logic against data facts efficiently. It supports dynamic system modeling by enabling runtime updates to policies and providing thread-safe knowledge ba
Evaluates incoming data streams against predefined logic patterns to trigger automated actions.
This project is a business rules and complex event processing engine designed to manage logical decision-making and stateful workflows. It functions as a computational framework that evaluates incoming data streams and facts against conditional logic to derive new conclusions and trigger automated actions. The engine distinguishes itself through a combination of forward-chaining inference and deterministic state machine orchestration. It uses salience-based conflict resolution to prioritize rule execution and supports persistent contextual state tracking to manage long-running business proces
Correlates event sequences and patterns to trigger automated actions based on logical and time-based constraints.