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Apache Storm VS Scilab

Compare Apache Storm VS Scilab 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.

Scilab logo Scilab

Scilab Official Website. Enter your search in the box aboveAbout ScilabScilab is free and open source software for numerical . Thanks for downloading Scilab!
  • Apache Storm Landing page
    Landing page //
    2019-03-11
  • Scilab Landing page
    Landing page //
    2023-02-10

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.

Scilab features and specs

  • Open Source
    Scilab is free and open-source software, allowing users to access the source code and modify it to suit their needs without any cost.
  • Extensive Mathematical Functionality
    Scilab provides a wide range of mathematical functions and capabilities for numerical computation, making it suitable for a variety of scientific and engineering applications.
  • Toolboxes and Modules
    It offers various built-in toolboxes and modules for specialized tasks, such as signal processing, control systems, and optimization, expanding its functionality.
  • Cross-Platform Support
    Scilab runs on different operating systems, including Windows, macOS, and Linux, providing flexibility for users working in diverse environments.
  • Strong Community Support
    A large and active user community means that users can find plenty of support, tutorials, and third-party contributions, easing the learning curve.
  • Integration Capabilities
    Scilab can be easily integrated with other software and tools, such as Modelica for modeling and simulation, enhancing its versatility in different workflows.

Possible disadvantages of Scilab

  • Performance
    Scilab may not be as performance-optimized as some other numerical computation software, like MATLAB, especially for very large datasets or highly complex calculations.
  • Learning Curve
    While Scilab is powerful, it can be challenging for beginners to master due to its extensive functionality and the need to learn its scripting language.
  • Less Commercial Support
    As open-source software, Scilab does not offer the same level of commercial support or extensive professional resources that are available for some paid alternatives like MATLAB.
  • Documentation Quality
    Although Scilab has a lot of documentation, some users find that it lacks depth or clarity compared to other software, making it harder to find thorough explanations or examples.
  • Graphical User Interface
    The graphical user interface (GUI) of Scilab is not as polished or user-friendly as that of some competitor tools, which can impact user experience.
  • Compatibility Issues
    Interoperability with MATLAB can be limited, potentially causing issues when porting code or collaborating with MATLAB users.

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

Scilab videos

+ Add

Scilab IPCV 1.2

More videos:

  • Review - Raspberry Pi for Computer Vision with Scilab
  • Review - Tone Recognition with Scilab and LabVIEW to Scilab Gateway

Category Popularity

0-100% (relative to Apache Storm and Scilab)

Apache Storm

Scilab

Big Data
100 100%
Big Data
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Stream Processing
100 100%
Stream Processing
0% 0
Numerical Computation
0 0%
Numerical Computation
100% 100

User comments

Share your experience with using Apache Storm and Scilab. For example, how are they different and which one is better?
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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 Scilab

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

Scilab Reviews

25 Best Statistical Analysis Software
Scilab is a powerful, free, and open-source software widely used by researchers, students, and professionals in various fields such as engineering, mathematics, physics, and more.
Source: www.scijournal.org
7 Best MATLAB alternatives for Linux
The syntax of Scilab is similar to MATLAB it also provides a source code translator to convert MATLAB code to Scilab.
Source: cyanogenmods.org
Matlab Alternatives
Scilab is an open-source similar to the implementation of Matlab. The approximation techniques known as Scientific Computing is used to solve numerical problems. To achieve this, the team of Scilab developers made use of Solvers and algorithms to build the algebraic libraries. Scilab is one of the major alternatives to Matlab along with GNU Octave.
Source: www.educba.com
10 Best MATLAB Alternatives [For Beginners and Professionals]
Scilab has 1700 mathematical functions for engineering applications and data analysis. You can also use Scilab to solve various constrained and unconstrained problems such as shape and topology optimizations etc.
Source: thetechtop10.com
4 open source alternatives to MATLAB
Scilab is another open source option for numerical computing that runs across all the major platforms: Windows, Mac, and Linux included. Scilab is perhaps the best known alternative outside of Octave, and (like Octave) it is very similar to MATLAB in its implementation, although exact compatibility is not a goal of the project's developers.
Source: opensource.com

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 2 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 2 years ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 2 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: over 2 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 3 years ago
View more

Scilab mentions (0)

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

What are some alternatives?

When comparing Apache Storm and Scilab, 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.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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

Wolfram Mathematica - Mathematica has characterized the cutting edge in specialized processing—and gave the chief calculation environment to a large number of pioneers, instructors, understudies, and others around the globe.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

GNU Octave - GNU Octave is a programming language for scientific computing.

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