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Apache Storm

4.8

Poor

Free Plan

language

description Apache Storm Overview

Apache Storm was one of the first distributed stream processing systems to gain widespread adoption. It provides a simple and robust way to process streams of data in real-time.

While it has been largely superseded by newer frameworks like Flink and Spark, it is still used in many legacy systems due to its simplicity and proven reliability. Storm is best suited for simple, low-latency streaming tasks where the complexity of modern frameworks is not required. It remains a foundational piece of history in the stream processing world.

recommend Best for: Ideal for organizations requiring high-performance real-time data processing in mission-critical applications.

info Apache Storm Specifications

Api	REST API for topology management and monitoring
Language	Supports Java, Python, Ruby
Platform	Java
Integration	Kafka, Redis, Cassandra, Hadoop

balance Apache Storm Pros & Cons

thumb_up Pros

check Scalable to handle large volumes of data
check Fault-tolerant with guaranteed exactly-once processing
check Supports real-time analytics and complex topology design
check Low latency for timely data processing

thumb_down Cons

close Steep learning curve due to complexity
close Resource-intensive, requiring significant computational power
close Limited community support compared to other frameworks
close Not ideal for batch processing tasks

help Apache Storm FAQ

What is Apache Storm used for?

Apache Storm is primarily used for real-time data processing and stream analytics in applications like financial trading systems.

Is Apache Storm free to use?

Yes, Apache Storm is open-source software with a freemium model that offers both free and paid support options.

Does Apache Storm have good community support?

While the core framework has strong documentation, community support can be limited compared to other popular frameworks.

What is Apache Storm?

Apache Storm was one of the first distributed stream processing systems to gain widespread adoption. It provides a simple and robust way to process streams of data in real-time. While it has been largely superseded by newer frameworks like Flink and Spark, it is still used in many legacy systems due to its simplicity and proven reliability. Storm is best suited for simple, low-latency streaming tasks where the complexity of modern frameworks is not required. It remains a foundational piece of history in the stream processing world.

How good is Apache Storm?

Apache Storm scores 4.8/10 (Poor) on Lunoo, making it rated in the Data Science category. Apache Storm scores 7.8/10 due to its robust fault-tolerance and scalability, which are critical for real-time applications. However, it has a steep l...

How much does Apache Storm cost?

Free Plan. Visit the official website for the most up-to-date pricing.

What are the best alternatives to Apache Storm?

See our alternatives page for Apache Storm for a ranked list with scores. Top alternatives include: Apache Pinot, Google Colab, Ursula K. Le Guin.

What is Apache Storm best for?

Ideal for organizations requiring high-performance real-time data processing in mission-critical applications.

How does Apache Storm compare to Apache Pinot?

See our detailed comparison of Apache Storm vs Apache Pinot with scores, features, and an AI-powered verdict.

Is Apache Storm worth it in 2026?

With a score of 4.8/10, Apache Storm is a solid option in Data Science. See all Data Science ranked.

What are the key specifications of Apache Storm?

API: REST API for topology management and monitoring
Language: Supports Java, Python, Ruby
Platform: Java
Integration: Kafka, Redis, Cassandra, Hadoop

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4.8

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Why this score

Apache Storm scores 4.8/10 due to its robust fault-tolerance and scalability, which are critical for real-time applications. However, it has a steep learning curve and limited community support, affecting its overall score.

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