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Airflow
Airflow

320
256
+ 1
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NSQ
NSQ

75
99
+ 1
127
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Airflow vs NSQ: What are the differences?

Developers describe Airflow as "A platform to programmaticaly author, schedule and monitor data pipelines, by Airbnb". Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed. On the other hand, NSQ is detailed as "A realtime distributed messaging platform". NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

Airflow and NSQ are primarily classified as "Workflow Manager" and "Message Queue" tools respectively.

Some of the features offered by Airflow are:

  • Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writting code that instantiate pipelines dynamically.
  • Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.
  • Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built in the core of Airflow using powerful Jinja templating engine.

On the other hand, NSQ provides the following key features:

  • support distributed topologies with no SPOF
  • horizontally scalable (no brokers, seamlessly add more nodes to the cluster)
  • low-latency push based message delivery (performance)

Airflow and NSQ are both open source tools. It seems that NSQ with 15.6K GitHub stars and 2.03K forks on GitHub has more adoption than Airflow with 12.9K GitHub stars and 4.71K GitHub forks.

Airbnb, Slack, and 9GAG are some of the popular companies that use Airflow, whereas NSQ is used by Stripe, Docker, and Segment. Airflow has a broader approval, being mentioned in 72 company stacks & 33 developers stacks; compared to NSQ, which is listed in 21 company stacks and 8 developer stacks.

What is Airflow?

Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.

What is NSQ?

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.
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    What tools integrate with Airflow?
    What tools integrate with NSQ?
      No integrations found
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        What are some alternatives to Airflow and NSQ?
        Luigi
        It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
        Apache NiFi
        An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
        Jenkins
        In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project.
        AWS Step Functions
        AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
        Apache Beam
        It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
        See all alternatives
        Decisions about Airflow and NSQ
        No stack decisions found
        Interest over time
        Reviews of Airflow and NSQ
        No reviews found
        How developers use Airflow and NSQ
        Avatar of InsideSales.com
        InsideSales.com uses NSQNSQ

        The built-in Gamification that comes with our Playbooks application uses NSQ for work queues and microservice communication.

        Avatar of Eugene Ivanchenko
        Eugene Ivanchenko uses AirflowAirflow

        Manage the calculation pipeline and data distribution procedures.

        Avatar of Christopher Davison
        Christopher Davison uses AirflowAirflow

        Used for scheduling ETL jobs

        How much does Airflow cost?
        How much does NSQ cost?
        Pricing unavailable
        Pricing unavailable
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