# alibaba/jstorm

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3,877 stars · 1,762 forks · Java · Apache-2.0 · archived

## Links

- GitHub: https://github.com/alibaba/jstorm
- Homepage: http://jstorm.io
- awesome-repositories: https://awesome-repositories.com/repository/alibaba-jstorm.md

## Description

jStorm is a distributed stream processing engine designed for executing low-latency computations on high-volume data streams using Apache Storm topologies. It functions as a real-time data analytics platform and distributed task orchestrator that manages complex data pipelines via directed acyclic graph execution.

The system provides a scalable framework for data pipeline management, incorporating backpressure-aware flow control to regulate ingestion rates and dynamic resource allocation to adjust computing resources based on real-time demand. It maintains compatibility with Apache Storm configurations for topology management and coordinates event-driven analytics infrastructure.

The platform covers a broad range of capabilities including high-throughput data ingestion and distributed pipeline orchestration. It ensures continuous processing through fault-tolerant task orchestration that detects component failures and restarts interrupted processes across server clusters.

## Tags

### Data & Databases

- [Stream Processing Engines](https://awesome-repositories.com/f/data-databases/data-processing-pipelines/data-processing-frameworks/stream-processing-engines.md) — Functions as a distributed engine that performs continuous computation on real-time data streams with low latency. ([source](https://cdn.jsdelivr.net/gh/alibaba/jstorm@master/README.md))
- [Apache Storm Topology Management](https://awesome-repositories.com/f/data-databases/apache-storm-topology-management.md) — Maintains compatibility with Apache Storm configurations for managing distributed data processing topologies.
- [Data Pipeline Orchestration](https://awesome-repositories.com/f/data-databases/data-pipeline-orchestration.md) — Coordinates complex data flows across server clusters with automated fault tolerance and task recovery.
- [Distributed Task Schedulers](https://awesome-repositories.com/f/data-databases/distributed-task-schedulers.md) — Orchestrates and distributes complex data processing workflows across computing clusters for horizontal scaling.
- [Real-time Analytics Platforms](https://awesome-repositories.com/f/data-databases/real-time-analytics-platforms.md) — Manages complex data pipelines and event-driven analytics through directed acyclic graph execution.
- [Real-Time Data Streaming](https://awesome-repositories.com/f/data-databases/real-time-data-streaming.md) — Analyzes high-volume data streams with low latency to derive insights from events as they occur.
- [Event Analytics](https://awesome-repositories.com/f/data-databases/event-analytics.md) — Builds scalable systems that trigger computations and analysis based on continuous streams of event data.
- [High-Throughput Ingestion Pipelines](https://awesome-repositories.com/f/data-databases/high-throughput-ingestion-pipelines.md) — Manages the flow of massive datasets into processing engines using backpressure control.
- [Production Data Pipeline Management](https://awesome-repositories.com/f/data-databases/production-data-pipeline-management.md) — Offers a pipeline framework with backpressure-aware flow control and dynamic resource allocation.

### DevOps & Infrastructure

- [Distributed Task Orchestrators](https://awesome-repositories.com/f/devops-infrastructure/distributed-task-orchestrators.md) — Provides an automated fault-tolerant manager that detects component failures and restarts processes across clusters.
- [Dynamic Resource Allocators](https://awesome-repositories.com/f/devops-infrastructure/resource-allocation/dynamic-resource-allocators.md) — Adjusts computing resources assigned to specific tasks based on real-time processing demand and load.

### Software Engineering & Architecture

- [Fault Tolerance](https://awesome-repositories.com/f/software-engineering-architecture/fault-tolerance.md) — Provides automated recovery mechanisms that detect component failures and restart interrupted processes.
- [Directed Acyclic Graph Pipelines](https://awesome-repositories.com/f/software-engineering-architecture/parallel-processing-pipelines/directed-acyclic-graph-pipelines.md) — Uses directed acyclic graphs to manage processing dependencies and define the flow of streaming data.
- [Backpressure Management](https://awesome-repositories.com/f/software-engineering-architecture/backpressure-management.md) — Implements systems for regulating data flow between producers and consumers to prevent resource exhaustion.

### Networking & Communication

- [Message-Passing Process Coordination](https://awesome-repositories.com/f/networking-communication/message-passing-process-coordination.md) — Uses an optimized inter-process communication layer to move data between distributed nodes with minimal latency.

### Part of an Awesome List

- [Big Data Frameworks](https://awesome-repositories.com/f/awesome-lists/data/big-data-frameworks.md) — Distributed and fault-tolerant real-time computation system.
- [Infrastructure and Backend](https://awesome-repositories.com/f/awesome-lists/devops/infrastructure-and-backend.md) — Enterprise-grade stream computing engine.