Apache Airflow vs. Informatica PowerCenter

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Airflow
Score 8.5 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
Informatica PowerCenter
Score 7.8 out of 10
N/A
Informatica PowerCenter is a metadata driven data integration technology designed to form the foundation for data integration initiatives, including analytics and data warehousing, application migration, or consolidation and data governance.N/A
Pricing
Apache AirflowInformatica PowerCenter
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache AirflowInformatica PowerCenter
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Apache AirflowInformatica PowerCenter
Top Pros
Top Cons
Features
Apache AirflowInformatica PowerCenter
Workload Automation
Comparison of Workload Automation features of Product A and Product B
Apache Airflow
8.2
9 Ratings
0% above category average
Informatica PowerCenter
-
Ratings
Multi-platform scheduling8.89 Ratings00 Ratings
Central monitoring8.49 Ratings00 Ratings
Logging8.19 Ratings00 Ratings
Alerts and notifications7.99 Ratings00 Ratings
Analysis and visualization7.99 Ratings00 Ratings
Application integration8.49 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Apache Airflow
-
Ratings
Informatica PowerCenter
8.5
18 Ratings
3% above category average
Connect to traditional data sources00 Ratings9.018 Ratings
Connecto to Big Data and NoSQL00 Ratings8.014 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Apache Airflow
-
Ratings
Informatica PowerCenter
7.5
18 Ratings
11% below category average
Simple transformations00 Ratings8.018 Ratings
Complex transformations00 Ratings7.018 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Apache Airflow
-
Ratings
Informatica PowerCenter
8.2
18 Ratings
1% above category average
Data model creation00 Ratings9.015 Ratings
Metadata management00 Ratings8.016 Ratings
Business rules and workflow00 Ratings9.018 Ratings
Collaboration00 Ratings6.116 Ratings
Testing and debugging00 Ratings9.017 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Apache Airflow
-
Ratings
Informatica PowerCenter
9.0
15 Ratings
9% above category average
Integration with data quality tools00 Ratings9.015 Ratings
Integration with MDM tools00 Ratings9.013 Ratings
Best Alternatives
Apache AirflowInformatica PowerCenter
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User Ratings
Apache AirflowInformatica PowerCenter
Likelihood to Recommend
7.8
(9 ratings)
8.0
(21 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(4 ratings)
Usability
-
(0 ratings)
9.0
(3 ratings)
Performance
-
(0 ratings)
9.4
(2 ratings)
Support Rating
-
(0 ratings)
9.0
(2 ratings)
User Testimonials
Apache AirflowInformatica PowerCenter
Likelihood to Recommend
Apache
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.
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Informatica
1.- Scenaries with poor sources of data is not recomended (Very bad ROI). The solution is for medium-big enterprises with a lot of sources of data and users. 2.- Bank and finance enviroment to integrate differente data form trading, Regulatory reports, decisions makers, fraud and financial crimes because in this kind of scenary the quality of data is the base of the business. 3.- Departments of development and test of applications in enterprises because you can design enviroments, out of the production systems, to development and test the new API's or updateds made.
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Pros
Apache
  • In charge of the ETL processes.
  • As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.
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Informatica
  • Informatica Powercenter is an innovative software that works with ETL-type data integration. Connectivity to almost all the database systems.
  • Great documentation and customer support.
  • It has a various solution to address data quality issues. data masking, data virtualization. It has various supporting tools or MDM, IDQ, Analyst, BigData which can be used to analyze data and correct it.
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Cons
Apache
  • they should bring in some time based scheduling too not only event based
  • they do not store the metadata due to which we are not able to analyze the workflows
  • they only support python as of now for scripted pipeline writing
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Informatica
  • There are too many ways to perform the same or similar functions which in turn makes it challenging to trace what a workflow is doing and at which point (ex. sessions can be designed as static or re-usable and the override can occur at the session or workflow, or both which can be counter productive and confusing when troubleshooting).
  • The power in structured design is a double edged sword. Simple tasks for a POC can become cumbersome. Ex. if you want to move some data to test a process, you first have to create your sources by importing them which means an ODBC connection or similar will need to be configured, you in turn have to develop your targets and all of the essential building blocks before being able to begin actual development. While I am on sources and targets, I think of a table definition as just that and find it counter intuitive to have to design a table as both a source and target and manage them as different objects. It would be more intuitive to have a table definition and its source/target properties defined by where you drag and drop it in the mapping.
  • There are no checkpoints or data viewer type functions without designing an entire mapping and workflow. If you would like to simply run a job up to a point and check the throughput, an entire mapping needs to be completed and you would workaround this by creating a flat file target.
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Likelihood to Renew
Apache
No answers on this topic
Informatica
Our team enjoys using Informatica and feels that it is one of the best ETL tools on the market.
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Usability
Apache
No answers on this topic
Informatica
Positives; - Multi User Development Environment - Speed of transformation - Seamless integration between other Informatica products. Negatives; - There should be less windows to maintain developers' focus while using. You probably need 2 big monitors when you start development with Informatica Power Center. - Oracle Analytical functions should be natively used. - E-LT support as well as ETL support.
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Performance
Apache
No answers on this topic
Informatica
PowerCenter is robust and fast, and it does a great job meeting all the needs, not just the most commercially vocal needs. In the hands of an expert power user, you can accomplish almost anything with your data. It is not for new users or intermittent users-- for that the Cloud version is a better fit. Be prepared for costly connectors (priced differently for each source or destination you are working with), and just be planful of your projects so you are not paying for connectors you no longer need or want
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Support Rating
Apache
No answers on this topic
Informatica
Informatica power center is a leader of the pack of ETL tools and has some great abilities that make it stand out from other ETL tools. It has been a great partner to its clients over a long time so it's definitely dependable. With all the great things about Informatica, it has a bit of tech burden that should be addressed to make it more nimble, reduce the learning curve for new developers, provide better connectivity with visualization tools.
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Alternatives Considered
Apache
There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.
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Informatica
While Talend offers a much more comfortable interface to work with, Informatica's forte is performance. And on that front, Informatica Enterprise Data Integration certainly leaves Talend in the dust. For a more back-end-centric use case, Informatica is certainly the ETL tool of choice. On the other hand, if business users would be using the tool, then Talend would be the preferred tool.
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Return on Investment
Apache
  • 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
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Informatica
  • The data pipeline automation capability of Informatica means that few resources are needed to pre-process the data that ultimately resides in a Data Warehouse. Once a workflow is implemented, manual intervention is not needed.
  • PowerCenter did require more resources and time for installation and configuration than was expected/planned for.
  • The lack of or minimal support of unstructured data means that newer sources of dynamic/changing data cannot be easily processed/transformed through PowerCenter workflows.
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