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Apache Storm VS gevent

Compare Apache Storm VS gevent and see what are their differences

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Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.

gevent logo gevent

gevent is a coroutine -based Python networking library that uses greenlet to provide a high-level...
  • Apache Storm Landing page
    Landing page //
    2019-03-11
  • gevent Landing page
    Landing page //
    2019-04-18

Apache Storm features and specs

  • Real-Time Processing
    Apache Storm is designed for processing data in real-time, which makes it ideal for applications like fraud detection, recommendation systems, and monitoring tools.
  • Scalability
    Storm is capable of scaling horizontally, allowing it to handle increasing amounts of data by adding more nodes, making it suitable for large-scale applications.
  • Fault Tolerance
    Storm provides robust fault-tolerance mechanisms by rerouting tasks from failed nodes to operational ones, ensuring continuous processing.
  • Broad Language Support
    Apache Storm supports multiple programming languages, including Java, Python, and Ruby, allowing developers to use the language they are most comfortable with.
  • Open Source Community
    Being an Apache project, Storm benefits from a strong open-source community, which contributes to its development and offers abundant resources and support.

Possible disadvantages of Apache Storm

  • Complex Setup
    Setting up and configuring Apache Storm can be complex and time-consuming, requiring detailed knowledge of its architecture and the underlying infrastructure.
  • High Learning Curve
    The architecture and components of Storm can be difficult for new users to grasp, leading to a steeper learning curve compared to some other streaming platforms.
  • Maintenance Overhead
    Managing and maintaining a Storm cluster can require significant effort, including monitoring, troubleshooting, and scaling the infrastructure.
  • Error Handling
    While Storm is fault-tolerant, its error handling at the application level can sometimes be challenging, requiring careful design to manage failures effectively.
  • Resource Intensive
    Storm can be resource-intensive, particularly in terms of memory and CPU usage, which can lead to increased costs and necessitate powerful hardware.

gevent features and specs

  • Concurrency
    Gevent allows you to handle concurrent tasks efficiently by using greenlets, which are lightweight pseudo-threads that can be scheduled and executed by the gevent scheduler. This leads to better resource utilization compared to traditional threads.
  • Low Latency
    Because gevent is based on a non-blocking I/O model, it provides low latency when handling I/O-bound tasks, making it ideal for network applications that require responsive performance.
  • Ease of Use
    Gevent is easy to integrate into Python applications due to its simple API that mimics the standard library in many ways, allowing developers to write asynchronous code more naturally.
  • Efficient Networking
    Gevent is particularly optimized for network I/O operations, making it highly suitable for applications like chat servers, web servers, and other real-time network services.
  • Scalability
    By using greenlets, gevent can manage a large number of tasks concurrently without the overhead associated with threading, enabling better scalability for high-demand applications.

Possible disadvantages of gevent

  • Blocking Code Issues
    Gevent requires code to be cooperative with its non-blocking event loop. Blocking operations can interrupt the event loop, leading to performance issues if not handled properly.
  • Compatibility
    Not all Python libraries are compatible with gevent, especially those that perform blocking I/O operations. This might necessitate finding alternative libraries or making modifications to achieve compatibility.
  • Debugging Complexity
    Debugging asynchronous applications can be more complex compared to synchronous ones. Identifying issues related to task scheduling and concurrency can be challenging in gevent.
  • CPU-bound Limitations
    Gevent is not ideal for CPU-bound tasks, as Python's Global Interpreter Lock (GIL) can become a bottleneck. In such cases, multi-processing or other forms of parallelism may be more appropriate.
  • Learning Curve
    While gevent's API is user-friendly, developers need to be familiar with asynchronous programming concepts and understand how to write cooperative, non-blocking code, which can be a learning curve for those who are new to it.

Apache Storm videos

Apache Storm Tutorial For Beginners | Apache Storm Training | Apache Storm Example | Edureka

More videos:

  • Review - Developing Java Streaming Applications with Apache Storm
  • Review - Atom Text Editor Option - Real-Time Analytics with Apache Storm

gevent videos

gevent (Lightning Talk)

More videos:

  • Review - Gevent
  • Review - Quick tips gevent|python|bignners

Category Popularity

0-100% (relative to Apache Storm and gevent)
Big Data
100 100%
0% 0
Web And Application Servers
Stream Processing
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Storm and gevent

Apache Storm Reviews

Top 15 Kafka Alternatives Popular In 2021
Apache Storm is a recognized, distributed, open-source real-time computational system. It is free, simple to use, and helps in easily and accurately processing multiple data streams in real-time. Because of its simplicity, it can be utilized with any programming language and that is one reason it is a developerโ€™s preferred choice. It is fast, scalable, and integrates well...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Storm is an open-source distributed real-time computational system for processing data streams. Similar to what Hadoop does for batch processing, Apache Storm does for unbounded streams of data in a reliable manner. Built by Twitter, Apache Storm specifically aims at the transformation of data streams. Storm has many use cases like real-time analytics, online machine...

gevent Reviews

We have no reviews of gevent yet.
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Social recommendations and mentions

Based on our record, Apache Storm seems to be more popular. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Storm mentions (11)

  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
  • Real Time Data Infra Stack
    Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years ago
  • Elon Musk reportedly wants to fire 75% of Twitterโ€™s employees
    Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: almost 4 years ago
  • Spark for beginners - and you
    Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
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gevent mentions (0)

We have not tracked any mentions of gevent yet. Tracking of gevent recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Storm and gevent, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Socket.io - Realtime application framework (Node.JS server)

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

WebSocket-Node - A WebSocket Implementation for Node.JS ( Draft -08 through the final RFC 6455 )

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

eventlet - Eventlet is a concurrent networking library for Python that allows you to change how you run your...