Storm

What it is

Storm is a distributed realtime computation system designed to process large streams of data in real-time. It provides fault-tolerance and scalability, making it suitable for applications that require low-latency processing of continuous data flows.

Storm stands out as a mature, open-source solution for processing large streams of data in real-time with guaranteed message processing and fault-tolerance, making it ideal for scalable applications requiring low-latency.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Steep learning curve for new users

   Storm's architecture and terminology are complex, requiring significant time investment to understand its inner workings.

2. 02

   Limited language support beyond Java

   While Storm provides a core Java API, support for other languages is limited or non-existent, constraining development flexibility.

3. 03

   Complex setup and configuration

   Setting up a Storm cluster requires configuring multiple components including ZooKeeper and Nimbus, which can be error-prone and time-consuming.

4. 04

   Performance bottlenecks in large-scale deployments

   In very large clusters or under heavy load, Storm's performance may degrade due to coordination overhead between nodes.

What it does well

• Distributed and fault-tolerant architecture

• Guaranteed message processing

• Scalability for handling large data streams

• Real-time computation capabilities

• Extensible with various programming languages

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.