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Apache Storm VS Portable Python

Compare Apache Storm VS Portable Python and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Storm logo Apache Storm

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

Portable Python logo Portable Python

Minimum bare bones portable python distribution with PyScripter as development environment.
  • Apache Storm Landing page
    Landing page //
    2019-03-11
  • Portable Python Landing page
    Landing page //
    2023-10-01

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.

Portable Python features and specs

  • Ease of Use
    Portable Python comes with everything configured and ready to run, making it easy for users to start working with Python without extensive setup.
  • Portability
    It can be run from a USB stick or any other portable device, which makes it convenient for use across different computers without installation.
  • Integrated Packages
    Includes a collection of Python packages and tools, such as PyCharm, PyQT, and Django, which streamlines the development process.
  • No Administrative Privileges Needed
    Users can run Portable Python without needing administrative privileges on Windows machines, making it accessible in restricted environments.

Possible disadvantages of Portable Python

  • Lack of Updates
    Portable Python is not frequently updated, which may lead to compatibility issues with newer Python projects and libraries.
  • Limited Support
    Being less popular compared to standard Python distributions, it may lack community support and comprehensive documentation.
  • Windows Only
    Portable Python is designed primarily for Windows environments, limiting its accessibility for users on other operating systems like macOS or Linux.
  • Dependency Conflicts
    Managing and updating packages may lead to conflicts, especially as the application ages and dependencies change over time.

Apache Storm videos

+ Add

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

Portable Python videos

No Portable Python videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Apache Storm and Portable Python)

Apache Storm

Portable Python

Big Data
100 100%
Big Data
0% 0
Text Editors
0 0%
Text Editors
100% 100
Stream Processing
100 100%
Stream Processing
0% 0
IDE
0 0%
IDE
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 Portable Python

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 developer’s preferred choice. It is fast, scalable, and integrates well...
Source: www.spec-india.com
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...
Source: www.analyticsinsight.net

Portable Python Reviews

We have no reviews of Portable Python yet.
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Social recommendations and mentions

Based on our record, Apache Storm should be more popular than Portable Python. 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 / almost 4 years ago
  • Elon Musk reportedly wants to fire 75% of Twitter’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
View more

Portable Python mentions (2)

  • Can my work till if I run Linux from a USB?
    Not likely, unless they were LOOKING for that kind of thing, which is also unlikely. However, many companies lock the bios to stop you changing the preferred boot order of the PC. You could also consider using Python Portable, therefore would not be actually installing anything https://sourceforge.net/projects/portable-python/. Source: almost 4 years ago
  • Problem with rembg and portable python 3.8.9 x64
    Hello, i'm a compelte noob in python and have a problem with run rembg with portable python 3.8.9x64 (downloaded from https://sourceforge.net/projects/portable-python/). Source: almost 5 years ago

What are some alternatives?

When comparing Apache Storm and Portable Python, 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.

WinPython - The easiest way to run Python, Spyder with SciPy and friends out of the box on any Windows PC...

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

PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...

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

Anaconda - Anaconda is the leading open data science platform powered by Python.

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