Software Alternatives, Accelerators & Startups

Dask VS MATLAB

Compare Dask VS MATLAB and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Dask logo Dask

Dask natively scales Python Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love

MATLAB logo MATLAB

A high-level language and interactive environment for numerical computation, visualization, and programming
  • Dask Landing page
    Landing page //
    2022-08-26
  • MATLAB Landing page
    Landing page //
    2022-10-30

We recommend LibHunt MATLAB for discovery and comparisons of trending MATLAB projects.

Dask features and specs

  • Parallel Computing
    Dask allows you to write parallel, distributed computing applications with task scheduling, enabling efficient use of computational resources for processing large datasets.
  • Scale
    It scales from a single machine to a large cluster, providing flexibility to develop code locally on a laptop and then deploy to cloud or other high-performance environments.
  • Integration with Existing Ecosystem
    Dask integrates well with popular Python libraries like NumPy, pandas, and Scikit-learn, allowing users to leverage existing code and skills while scaling to larger datasets.
  • Flexibility
    Dask can handle both data parallel and task parallel workloads, giving developers the freedom to implement various algorithms and solutions efficiently.
  • Dynamic Task Scheduling
    Dask's dynamic task scheduler optimizes the execution of tasks based on available resources, reducing malfunction risks and improving resource utilization.

Possible disadvantages of Dask

  • Complexity in Setup
    Setting up Dask, particularly in distributed settings, can be complex and may require significant infrastructure management efforts.
  • Performance Overhead
    While Dask provides high-level abstractions for parallel computing, there can be performance overhead due to its abstractions and scheduling mechanics which might not match the performance of highly optimized, low-level code.
  • Limited Support for Some Libraries
    Dask's smart parallelization might not perfectly support all features of libraries like pandas or NumPy, potentially requiring workarounds.
  • Learning Curve
    Despite its integration with Python's data science stack, Dask presents a learning curve for those unfamiliar with parallel computing concepts.
  • Debugging Challenges
    Debugging parallel computations can be more challenging compared to single-threaded applications, and users need to understand the distributed computation model.

MATLAB features and specs

  • Versatility
    MATLAB is versatile and can be used across a wide range of applications, including engineering, data analysis, robotics, and image processing.
  • Built-in Functions
    MATLAB comes with a vast library of built-in functions and toolboxes that simplify complex mathematical computations and data visualization tasks.
  • User-Friendly Interface
    The software offers an intuitive and user-friendly graphical interface that makes it accessible even for those who are not experts in programming.
  • Excellent Visualization
    MATLAB provides high-quality, customizable plots and graphs that facilitate the clear and effective presentation of data.
  • Strong Community and Support
    Users can benefit from extensive documentation, community forums, and customer support from MathWorks, which aids in troubleshooting and learning.
  • Integration Capabilities
    MATLAB integrates well with other programming languages like C, C++, and Java, and supports interfaces to SQL databases.

Possible disadvantages of MATLAB

  • Cost
    MATLAB is expensive to license, making it less accessible for small businesses, individual professionals, and students without institutional access.
  • Memory Usage
    MATLAB can be very memory-intensive, which could be a limitation when dealing with large datasets or running on devices with limited computational resources.
  • Speed
    Although MATLAB is efficient for rapid prototyping, it is generally slower in execution speed compared to compiled languages like C or Fortran, particularly for heavy computations.
  • Proprietary Nature
    Being a proprietary software, MATLAB does not offer the same level of transparency and flexibility that open-source alternatives provide.
  • Learning Curve
    For some new users, especially those who have no prior experience with numerical computing environments, it might have a steep learning curve.
  • Limited Cross-Platform Compatibility
    While MATLAB supports multiple operating systems, not all features and toolboxes are available on each platform, potentially limiting its utility in diverse environments.

Analysis of MATLAB

Overall verdict

  • Yes, MATLAB is considered a good tool by many professionals and academics, especially in fields that require numerical computation and data analysis.

Why this product is good

  • MATLAB offers a vast collection of built-in functions and toolboxes for various applications like signal processing, image processing, machine learning, and more.
  • The environment is user-friendly and has excellent documentation, making it easier for beginners to learn.
  • It provides robust support for matrix operations, which is beneficial for linear algebra tasks and scientific computations.
  • MATLAB integrates well with languages like C/C++, Python, and Java, allowing for flexible development options.

Recommended for

  • Engineers and scientists performing complex mathematical calculations and simulations.
  • Students and educators in academic settings who require a reliable tool for teaching and learning mathematical concepts.
  • Researchers and data analysts looking to rapidly prototype algorithms and visualize data.
  • Professionals dealing with industries like aerospace, automotive, communications, and finance where rigorous data analysis is required.

Dask videos

DASK and Apache SparkGurpreet Singh Microsoft Corporation

More videos:

  • Review - VLOGTOBER : dask kitchen review ,groceries ,drinks
  • Review - Dask Futures: Introduction

MATLAB videos

Matlab Review Part 1

More videos:

  • Review - The Complete MATLAB Course: Beginner to Advanced!
  • Tutorial - Complete MATLAB Tutorial for Beginners

Category Popularity

0-100% (relative to Dask and MATLAB)
Workflows
100 100%
0% 0
Technical Computing
0 0%
100% 100
Databases
100 100%
0% 0
Numerical Computation
0 0%
100% 100

User comments

Share your experience with using Dask and MATLAB. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Dask and MATLAB

Dask Reviews

Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
Dask: You can use Dask for Parallel computing via task scheduling. It can also process continuous data streams. Again, this is part of the "Blaze Ecosystem."
Source: www.xplenty.com

MATLAB Reviews

25 Best Statistical Analysis Software
MATLAB is an exceptional choice for individuals seeking to perform advanced statistical analysis and data visualization. Its high-level programming environment and comprehensive range of tools enable users to efficiently process, analyze, and visualize their data.
7 Best MATLAB alternatives for Linux
MATLAB is a programming language and numeric computing environment. It is used for solving mathematical problems and displaying the result graphically. MATLAB is a paid tool, they provide a free trial for one month.
15 data science tools to consider using in 2021
Developed and sold by software vendor MathWorks since 1984, Matlab is a high-level programming language and analytics environment for numerical computing, mathematical modeling and data visualization. It's primarily used by conventional engineers and scientists to analyze data, design algorithms and develop embedded systems for wireless communications, industrial control,...
The 16 Best Data Science and Machine Learning Platforms for 2021
Description: MathWorks MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, tested, and...
Matlab Alternatives
Matrix Laboratory also known as MATLAB is a high-level programming language. It provides an interactive environment to perform computations in various fields such as mathematics, sciences and engineering streams. The results can be visualized and generated as reports for further analysis. Matlab is the pioneer in combining these things. A team of professionals develop the...
Source: www.educba.com

Social recommendations and mentions

Based on our record, Dask seems to be more popular. It has been mentiond 16 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.

Dask mentions (16)

  • Large Scale Hydrology: Geocomputational tools that you use
    We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk. Source: over 3 years ago
  • msgspec - a fast & friendly JSON/MessagePack library
    I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec. Source: over 3 years ago
  • What does it mean to scale your python powered pipeline?
    Dask: Distributed data frames, machine learning and more. - Source: dev.to / almost 4 years ago
  • Data pipelines with Luigi
    To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:. - Source: dev.to / almost 4 years ago
  • How to load 85.6 GB of XML data into a dataframe
    Iโ€™m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: almost 4 years ago
View more

MATLAB mentions (0)

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

What are some alternatives?

When comparing Dask and MATLAB, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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

NumPy - NumPy is the fundamental package for scientific computing with Python

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

PySpark - PySpark Tutorial - Apache Spark is written in Scala programming language. To support Python with Spark, Apache Spark community released a tool, PySpark. Using PySpark, you can wor

Scilab - Scilab Official Website. Enter your search in the box aboveAbout ScilabScilab is free and open source software for numerical . Thanks for downloading Scilab!