Based on our record, Apache Airflow should be more popular than Spring Framework. It has been mentiond 67 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.
We had to write our own frameworks (uphill, both ways) but most current frameworks will have similar documentation pages as well. Both Apache and Spring are especially good at that. - Source: dev.to / over 1 year ago
Framework link: https://spring.io/projects/spring-framework Github Link: https://github.com/spring-projects/spring-framework. - Source: dev.to / almost 2 years ago
A common used Java framework is Spring framework (ie https://spring.io/projects/spring-framework and short tutorials at https://www.baeldung.com/spring-intro). Source: almost 2 years ago
The most popular libraries are Spring Boot, which I mentioned above, and the[ Spring Framework](https://spring.io/projects/spring-framework), which makes it easy to start an application with different objects for different environments (e.g. You make a blueprint for objects that are used in a testing environment, and a separate one with objects for the prod environment). Source: almost 2 years ago
Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform. Source: almost 2 years ago
An integral part of an ML project is data acquisition and data transformation into the required format. This involves creating ETL (extract, transform, load) pipelines and running them periodically. Airflow is an open source platform that helps engineers create and manage complex data pipelines. Furthermore, the support for Python programming language makes it easy for ML teams to adopt Airflow. - Source: dev.to / 8 days ago
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / about 1 month ago
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 / 4 months ago
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: 7 months ago
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 / 7 months ago
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Make.com - Tool for workflow automation (Former Integromat)