Apache Airflow vs. Informatica PowerCenter (legacy)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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.N/A
Informatica PowerCenter (legacy)
Score 8.9 out of 10
N/A
Informatica PowerCenter was data integration technology designed to form the foundation for data integration initiatives, application migration, or analytics. It is a legacy product.N/A
Pricing
Apache AirflowInformatica PowerCenter (legacy)
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache AirflowInformatica PowerCenter (legacy)
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 (legacy)
Features
Apache AirflowInformatica PowerCenter (legacy)
Workload Automation
Comparison of Workload Automation features of Product A and Product B
Apache Airflow
8.7
12 Ratings
3% above category average
Informatica PowerCenter (legacy)
-
Ratings
Multi-platform scheduling9.312 Ratings00 Ratings
Central monitoring9.012 Ratings00 Ratings
Logging8.612 Ratings00 Ratings
Alerts and notifications9.312 Ratings00 Ratings
Analysis and visualization6.912 Ratings00 Ratings
Application integration9.312 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Apache Airflow
-
Ratings
Informatica PowerCenter (legacy)
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 (legacy)
7.5
18 Ratings
7% 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 (legacy)
8.2
18 Ratings
5% 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 (legacy)
9.0
15 Ratings
12% above category average
Integration with data quality tools00 Ratings9.015 Ratings
Integration with MDM tools00 Ratings9.013 Ratings
Best Alternatives
Apache AirflowInformatica PowerCenter (legacy)
Small Businesses

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Score 10.0 out of 10
Medium-sized Companies
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Score 7.6 out of 10
IBM InfoSphere Information Server
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Score 8.0 out of 10
Enterprises
Control-M
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Score 9.3 out of 10
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Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache AirflowInformatica PowerCenter (legacy)
Likelihood to Recommend
8.8
(12 ratings)
8.0
(21 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(4 ratings)
Usability
8.3
(3 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 (legacy)
Likelihood to Recommend
Apache
Airflow is well-suited for data engineering pipelines, creating scheduled workflows, and working with various data sources. You can implement almost any kind of DAG for any use case using the different operators or enforce your operator using the Python operator with ease. The MLOps feature of Airflow can be enhanced to match MLFlow-like features, making Airflow the go-to solution for all workloads, from data science to data engineering.
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Discontinued Products
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
  • 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.
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Discontinued Products
  • 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.
Read full review
Cons
Apache
  • UI/Dashboard can be updated to be customisable, and jobs summary in groups of errors/failures/success, instead of each job, so that a summary of errors can be used as a starting point for reviewing them.
  • Navigation - It's a bit dated. Could do with more modern web navigation UX. i.e. sidebars navigation instead of browser back/forward.
  • Again core functional reorg in terms of UX. Navigation can be improved for core functions as well, instead of discovery.
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Discontinued Products
  • 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
Discontinued Products
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
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.
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Discontinued Products
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
Discontinued Products
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
Discontinued Products
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
Multiple DAGs can be orchestrated simultaneously at varying times, and runs can be reproduced or replicated with relative ease. Overall, utilizing Apache Airflow is easier to use than other solutions now on the market. It is simple to integrate in Apache Airflow, and the workflow can be monitored and scheduling can be done quickly using Apache Airflow. We advocate using this tool for automating the data pipeline or process.
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Discontinued Products
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
  • 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
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Discontinued Products
  • 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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