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Spring Batch VS Apache Airflow

Compare Spring Batch VS Apache Airflow and see what are their differences

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Spring Batch

Level up your Java code and explore what Spring can do for you.

Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • Spring Batch Landing page
    Landing page //
    2023-08-26
  • Apache Airflow Landing page
    Landing page //
    2023-06-17

Spring Batch

Categories
  • Workflow Automation
  • Databases
  • Data Dashboard
  • ETL
Website spring.io  
Details $-

Apache Airflow

Categories
  • Workflow
  • Workflow Automation
  • Data Pipelines
  • ETL
  • Automation
Website airflow.apache.org  
Details $

Spring Batch videos

+ Add

Spring Batch Scheduling

More videos:

  • Review - ETE 2012 - Josh Long - Behind the Scenes of Spring Batch

Apache Airflow videos

+ Add

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

0-100% (relative to Spring Batch and Apache Airflow)

Spring Batch

Apache Airflow

Databases
100 100%
Databases
0% 0
Workflow Automation
5 5%
Workflow Automation
95% 95
Automation
0 0%
Automation
100% 100
ETL
100 100%
ETL
0% 0

User comments

Share your experience with using Spring Batch and Apache Airflow. 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 Spring Batch and Apache Airflow

Spring Batch Reviews

We have no reviews of Spring Batch yet.
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Apache Airflow Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
Source: www.datacamp.com
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Airflow programmatically creates, schedules and monitors workflows. It can also modify the scheduler to run the jobs as and when required.
Source: www.softwaretestinghelp.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When does Apache Airflow make sense? If you're performing long ETL jobs or your ETL has multiple steps, Airflow will let you restart from any point during the ETL process. That being said, Apache Airflows IS NOT a library, so it has to be deployed and may make less sense on small ETL jobs.
Source: www.xplenty.com
Comparison of Python pipeline packages: Airflow, Luigi, Gokart, Metaflow, Kedro, PipelineX
Not designed to pass data between dependent tasks without using a database. There is no good way to pass unstructured data (e.g. image, video, pickle, etc.) between dependent tasks in Airflow.
Source: medium.com

Social recommendations and mentions

Based on our record, Apache Airflow seems to be a lot more popular than Spring Batch. While we know about 65 links to Apache Airflow, we've tracked only 2 mentions of Spring Batch. 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.

Spring Batch mentions (2)

Apache Airflow mentions (65)

  • The 2024 Web Hosting Report
    For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 13 days ago
  • Best ETL Tools And Why To Choose
    Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 4 months ago
  • Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
    Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 4 months ago
  • Share Your favorite python related software!
    AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 5 months ago
  • Ask HN: What is the correct way to deal with pipelines?
    I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 5 months ago
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What are some alternatives?

When comparing Spring Batch and Apache Airflow, 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.

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

Apache Kylin - OLAP Engine for Big Data

Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Make.com - Tool for workflow automation (Former Integromat)

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