Airflow VS Apache Camel

Compare Airflow vs Apache Camel and see what are their differences.

Airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows (by apache)

Apache Camel

Apache Camel is an open source integration framework that empowers you to quickly and easily integrate various systems consuming or producing data. (by apache)
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Airflow Apache Camel
151 18
29,553 4,778
2.2% 1.9%
10.0 10.0
6 days ago 6 days ago
Python Java
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Airflow

Posts with mentions or reviews of Airflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-19.

Apache Camel

Posts with mentions or reviews of Apache Camel. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-12.
  • Why messaging is much better than REST for inter-microservice communications
    9 projects | news.ycombinator.com | 12 Feb 2023
    This reminds me more of Apache Camel[0] than other things it's being compared to.

    > The process initiator puts a message on a queue, and another processor picks that up (probably on a different service, on a different host, and in different code base) - does some processing, and puts its (intermediate) result on another queue

    This is almost exactly the definition of message routing (ie: Camel).

    I'm a bit doubtful about the pitch because the solution is presented as enabling you to maintain synchronous style programming while achieving benefits of async processing. This just isn't true, these are fundamental tradeoffs. If you need a synchronous answer back then no amount of queuing, routing, prioritisation, etc etc will save you when the fundamental resource providing that is unavailable, and the ultimate outcome that your synchronous client now hangs indefinitely waiting for a reply message instead of erroring hard and fast is not desirable at all. If you go into this ad hoc, and build in a leaky abstraction that asynchronous things are are actually synchronous and vice versa, before you know it you are going to have unstable behaviour or even worse, deadlocks all over your system and the worst part - the true state of the system is now hidden in which messages are pending in transient message queues everywhere.

    What really matters here is to fundamentally design things from the start with patterns that allow you to be very explicit about what needs to be synchronous vs async (building on principles of idempotency, immutability, coherence, to maximise the cases where async is the answer).

    The notion of Apache Camel is to make all these decisions a first class elements of your framework and then to extract out the routing layer as a dedicated construct. The fact it generalises beyond message queues (treating literally anything that can provide a piece of data as a message provider) is a bonus.

    [0] https://camel.apache.org/

  • S3 to S3 transform
    3 projects | reddit.com/r/dataengineering | 21 Jan 2023
    For a simple sequential Pipeline, my goto would be Apache Camel. As soon as you want complexity its either Apache Nifi or a micro service architecture.
  • 🗞️ We have just released our JBang! catalog 🛍️
    6 projects | dev.to | 23 Nov 2022
    🐪 Apache Camel : Camel JBang, A JBang-based Camel app for easily running Camel routes.
  • 7GUIs of Java/Object Oriented Design?
    4 projects | reddit.com/r/java | 19 Nov 2022
  • Message broker as service integrator
    2 projects | reddit.com/r/devops | 30 Jul 2022
  • Apache Airflow 2.3.0 is out !
    2 projects | reddit.com/r/Python | 2 May 2022
    Sounds like Camel.
  • Open source Java projects
    5 projects | reddit.com/r/java | 24 Feb 2022
    Camel
  • What tools to use for small in house applications?
    2 projects | reddit.com/r/AskProgramming | 21 May 2021
    If you need to stick with spreadsheets I agree with the suggestion of Python--or Java, I used to automate a bunch of business processes with Apache Camel.
  • Im making a FME open source clone
    4 projects | reddit.com/r/gis | 5 May 2021
    Or if you are looking for something light-weighter you can always use Camel camel.apache.org
  • Steps to upgrade spring-boot 1.x to 2.x
    2 projects | dev.to | 13 Apr 2021
    apache camel dependency on spring boot, Kafka etc, also other libs dependencies Note: Kafka 1.1: https://mvnrepository.com/artifact/org.apache.camel/camel-kafka/2.22.4 kafka 2.0 : https://mvnrepository.com/artifact/org.apache.camel/camel-kafka/2.23.1 https://github.com/apache/camel/blob/master/components/camel-kafka/src/main/docs/kafka-component.adoc

What are some alternatives?

When comparing Airflow and Apache Camel you can also consider the following projects:

Kedro - A Python framework for creating reproducible, maintainable and modular data science code.

dagster - An orchestration platform for the development, production, and observation of data assets.

luigi - Luigi 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.

n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.

Dask - Parallel computing with task scheduling

Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing

airbyte - Data integration platform for ELT pipelines from APIs, databases & files to warehouses & lakes.

Apache Kafka - Mirror of Apache Kafka

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

argo - Workflow engine for Kubernetes

Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system

Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing