TrustRadius

5x vs. Apache Airflow

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
5x
Score 0.0 out of 10
N/A
5x is presented as a Modern Data Stack Platform that uses API’s to manage data infrastructure. These support automated vendor provisioning, 1-click integrations, consolidated billing, and role based access control. New vendors are added with a single click, and vendors are pre-vetted by 5x for their security practices. It is a managed service that enables companies to answer business questions, without having to worry about building data infrastructure or bringing in the right data engineering…N/A
Apache Airflow
Score 8.6 out of 10
N/A
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.N/A
Pricing
5xApache Airflow
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
5xApache Airflow
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
5xApache Airflow
Features
5xApache Airflow
Workload Automation
Comparison of Workload Automation features of Product A and Product B
5x
-
Ratings
Apache Airflow
9.8
Ratings
17% above category average
Multi-platform scheduling00 Ratings10.00 Ratings
Central monitoring00 Ratings10.00 Ratings
Logging00 Ratings10.00 Ratings
Alerts and notifications00 Ratings10.00 Ratings
Analysis and visualization00 Ratings10.00 Ratings
Application integration00 Ratings9.00 Ratings
Best Alternatives
5xApache Airflow
Small Businesses
Skyvia
Skyvia
Score 9.9 out of 10

No answers on this topic

Medium-sized Companies
Astera Data Pipeline Builder (Centerprise)
Astera Data Pipeline Builder (Centerprise)
Score 8.7 out of 10
ActiveBatch Workload Automation
ActiveBatch Workload Automation
Score 7.5 out of 10
Enterprises
Control-M
Control-M
Score 9.3 out of 10
Control-M
Control-M
Score 9.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
5xApache Airflow
Likelihood to Recommend
-
(0 ratings)
9.1
(0 ratings)
Usability
-
(0 ratings)
10.0
(0 ratings)
User Testimonials
5xApache Airflow
Likelihood to Recommend
No answers on this topic
For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.
VT
Victor Tay
Engineer
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Pros
No answers on this topic
  • Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
  • Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
  • Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.
RS
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Cons
No answers on this topic
  • A local "dry run" or IDE plugin that can validate and simulate DAG execution without needing a full environment.
  • Better feedback on DAG parse errors in the UI or CLI.
  • Navigating large DAGs with hundreds of tasks can be slow and hard to understand visually.
Verified User
Anonymous
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Usability
No answers on this topic
For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.
Verified User
Anonymous
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Alternatives Considered
No answers on this topic
Apache Airflow is suited for a much wider set of use cases compared to Databricks. You can run it anywhere, and there is also no vendor lock-in. With Airflow, we can utilize almost any compute engine. Same thing we want to do with Databricks. There might be some level of difficulty based on the support.
RS
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Return on Investment
No answers on this topic
  • 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.
Verified User
Anonymous
Read full review
ScreenShots