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Apache Storm VS Dask

Compare Apache Storm VS Dask and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Storm logo Apache Storm

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

Dask logo Dask

Dask natively scales Python Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love
  • Apache Storm Landing page
    Landing page //
    2019-03-11
  • Dask Landing page
    Landing page //
    2022-08-26

Apache Storm videos

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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

Dask videos

+ Add

DASK and Apache SparkGurpreet Singh Microsoft Corporation

More videos:

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

Category Popularity

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

Apache Storm

Dask

Big Data
100 100%
Big Data
0% 0
Workflows
0 0%
Workflows
100% 100
Databases
60 60%
Databases
40% 40
Stream Processing
100 100%
Stream Processing
0% 0

User comments

Share your experience with using Apache Storm and Dask. 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 Dask

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

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

Social recommendations and mentions

Dask might be a bit more popular than Apache Storm. We know about 16 links to it since March 2021 and only 11 links to Apache Storm. 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 1 year 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 1 year ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year 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 1 year 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 2 years ago
View more

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: about 2 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: about 2 years ago
  • What does it mean to scale your python powered pipeline?
    Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 2 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 / over 2 years ago
  • How to load 85.6 GB of XML data into a dataframe
    I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: over 2 years ago
View more

What are some alternatives?

When comparing Apache Storm and Dask, 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.

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

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

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

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

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

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