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Apache Storm
Distributed real-time stream processing engine for low-latency analytics
Apache Storm delivers scalable, fault-tolerant real-time computation across any language, enabling sub-second analytics and event-driven pipelines for enterprises with robust operational support.
Overview
Overview
Apache Storm is a distributed system that enables real‑time computation at scale. It targets developers and data engineers who need sub‑second latency for event‑driven applications, from fraud detection to live dashboards. The platform is language‑agnostic, allowing components to be written in Java, Python, Ruby, or any language that can speak its multilang protocol.
Capabilities & Deployment
Storm provides primitives for defining topologies—directed graphs of spouts (data sources) and bolts (processing units). Its fault‑tolerance model automatically retries failed tuples and rebalances workloads across a cluster managed by Apache Zookeeper. Deployments can run on bare‑metal, virtual machines, or container orchestration platforms, with extensive documentation and community mailing lists to assist operations.
Community & Support
Backed by the Apache Software Foundation, Storm benefits from a mature codebase, active mailing lists for users, developers, and issue tracking on GitHub, and commercial backing from contributors such as YourKit. This ecosystem makes it a reliable choice for enterprises seeking a proven streaming engine.
Highlights
True real‑time processing with sub‑second latency
Language‑agnostic multilang API for any programming language
Fault‑tolerant topology execution with automatic retries
Scalable architecture that integrates with Zookeeper for coordination
Pros
- Low latency suitable for time‑critical analytics
- Proven at scale in many production environments
- Strong open‑source community and extensive documentation
- Flexible integration with diverse data sources
Considerations
- Operational complexity requires Zookeeper and cluster management
- Core is Java‑centric, which may affect non‑Java teams
- Steeper learning curve for designing reliable topologies
- Limited built‑in UI compared with newer streaming platforms
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When teams consider Apache Storm, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- Enterprises needing sub‑second event processing
- Teams with existing Java or multilang expertise
- Applications that require fault‑tolerant streaming pipelines
- Organizations that can manage a distributed cluster
Not ideal when
- Pure batch processing workloads
- Small projects lacking operational resources
- Teams preferring fully managed cloud streaming services
- Use cases demanding complex stateful processing beyond Storm's primitives
How teams use it
Real‑time fraud detection
Immediate identification and alerting of suspicious transactions
Clickstream analytics
Live dashboards that reflect user behavior as it happens
IoT sensor aggregation
Continuous processing of sensor streams for downstream analytics
Dynamic recommendation updates
On‑the‑fly model refreshes that improve personalization in real time
Tech snapshot
Java84%
Python8%
HTML4%
Clojure2%
C2%
JavaScript1%
Frequently asked questions
Which programming languages can I use with Storm?
Storm supports any language via its multilang protocol; common choices include Java, Python, Ruby, and Clojure.
How does Storm achieve fault tolerance?
It tracks tuple acknowledgments, retries failed processing, and rebalances workloads automatically across the cluster.
What infrastructure is required to run Storm?
A Storm cluster needs Apache Zookeeper for coordination, plus worker nodes that run the topology processes.
How does Storm differ from Spark Streaming?
Storm processes each event as it arrives (true real‑time), whereas Spark Streaming works in micro‑batches.
Where can I get help or report issues?
Use the user@storm.apache.org mailing list for general questions, dev@storm.apache.org for development topics, and GitHub Issues for bugs and feature requests.
Project at a glance
Active- Stars
- 6,669
- Watchers
- 6,669
- Forks
- 4,054
LicenseApache-2.0
Repo age12 years old
Last commit2 days ago
Primary languageJava
Last synced yesterday