Apache Airflow for Startups
Used Airflow for Analytics & Reporting
Overview
What is Apache Airflow?
Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s…
Recent Reviews
Awards
Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards
Popular Features
- Multi-platform scheduling (9)8.888%
- Central monitoring (9)8.484%
- Logging (9)8.181%
- Alerts and notifications (9)7.979%
Reviewer Pros & Cons
Pricing
N/A
Unavailable
What is Apache Airflow?
Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s Incubator Program 2016 and announced as Top…
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Would you like us to let the vendor know that you want pricing?
28 people also want pricing
Alternatives Pricing
N/A
Unavailable
What is Control-M?
Control-M from BMC is a platform for integrating, automating, and orchestrating application and data workflows in production across complex hybrid technology ecosystems. It provides deep operational capabilities, delivering speed, scale, security, and governance.
What is Superblocks?
Superblocks is an IDE for internal tooling – a programmable set of building blocks for developers to create mission-critical internal operational software. The Superblocks Application Builder to assemble flexible components and connect to databases and APIs. Users can create REST, GraphQL, and gPRC…
Product Demos
Getting Started with Apache Airflow
YouTube
Apache Airflow | Build your custom operator for twitter API
YouTube
Features
Return to navigation
Product Details
- About
- Tech Details
- FAQs
What is Apache Airflow?
Apache Airflow Video
What's coming in Airflow 2.0?
Apache Airflow Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Frequently Asked Questions
Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s Incubator Program 2016 and announced as Top-Level Apache Project in 2019. It is used as a data orchestration solution, with over 140 integrations and community support.
Reviewers rate Multi-platform scheduling highest, with a score of 8.8.
The most common users of Apache Airflow are from Enterprises (1,001+ employees).
Comparisons
Compare with
Reviews and Ratings
(36)
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Recommendations
Apache Airflow has proven to be a versatile solution for managing and orchestrating various data tasks. Users have utilized this product as a core component for scheduling and monitoring scheduled jobs, inspecting job successes and failures, and troubleshooting errors or failures. It has also been extensively employed in GCP as part of Cloud Composer for running ETL jobs, streamlining data pipelines, and creating workflows for analytics and reporting.
Reviewers have found Apache Airflow to be an easy-to-configure and setup solution, making it ideal for orchestrating data flows and building enterprise data pipelines. Its ability to integrate with third-party solutions via APIs allows for seamless data access and integration. Users have also appreciated the product's capability to manage ETL pipelines and programmatically monitor data pipelines.
Another valuable use case of Apache Airflow is its role in creating workflows, orchestrating data pipelines, and automating tasks. Its flexibility has been particularly beneficial when dealing with complex data pipelines from diverse sources. Furthermore, the product has been effective in performing data integration in AWS S3 region, connecting to relational databases, executing data extracts, and compiling them into multiple flat file segments.
Apache Airflow brings standardization and modularity to data pipelines, enabling the implementation of complex pipelines and facilitating the sharing of data with partners as well as scoring machine learning models. Overall, users have found this product to be a valuable tool for managing data tasks efficiently and effectively.
Based on user reviews, here are the most common recommendations for Apache Airflow:
-
Read the documentation and take an introduction course to fully understand Airflow's behavior and close any knowledge gaps.
-
Consider Airflow as a first choice for ETL tasks that require programming. However, keep in mind that the coding aspect may not be suitable for all ETL engineers.
-
Replace cron jobs with Airflow for better results, utilizing its scheduling and dependency management features.
Overall, these recommendations emphasize the importance of familiarizing oneself with the documentation, leveraging Airflow's capabilities for programming-centric ETL tasks, and using it to replace traditional cron jobs.
Reviews
(1-9 of 9)Companies can't remove reviews or game the system. Here's why
March 06, 2024
Apache Airflow for Startups
- Impact Depends on number of workflows. If there are lot of workflows then it has a better usecase as the implementation is justified as it needs resources , dedicated VMs, Database that has a cost
- Donot use it if you have very less usecases
July 05, 2022
We used it to manage processes for etl pipelines
- Most of the ETL processes were automated, cutting down on human labor.
- Apache Airflow's user interface (UI) was very informative and straightforward.
- Since ETL processes were providing data via airflow, we were able to gain a deeper comprehension of the data at hand.
June 26, 2022
Apache AirFlow - Love the Features, Love the Reliability.. Love if the UI get modenized!
- It is a good workflow job scheduler.
- It meets all, if not most of our organization product requirements.
- AirFlow stability in terms of the product reliability is unmatched.
June 24, 2022
Apache Airflow is flawless
- A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
- Allowed us to implement complex data pipelines easily and at a relatively low cost
- Very quick to setup and integrate
- Good user community
- Agility to develop data workflows improved
June 21, 2022
Apache Airflow software
- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc).
- For ETL pipelines that extract batch data from multiple sources, and run Spark jobs or other data transformations.
- It also helps to generate report automatically.
- Triggering ETL jobs based on events
- running DAGs in a scheduled fashion
May 05, 2022
Apache Airflow for Automation and scheduling
- Overall positive impact using apache airflow
- Easy to use
- Easy to integrate which saves time
April 04, 2022
Apache Airflow
- We had a better understanding of data as ETL pipelines were giving data using airflow
- We were able to automate most of the ETL pipelines so it reduced manual efforts
- Airflow UI was extremely helpful which made it easy to understand