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Informatica PowerCenter vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Informatica PowerCenter
Ranking in Data Integration
4th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
83
Ranking in other categories
Data Visualization (11th)
Spring Cloud Data Flow
Ranking in Data Integration
21st
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (10th)
 

Mindshare comparison

As of November 2025, in the Data Integration category, the mindshare of Informatica PowerCenter is 5.3%, down from 10.8% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.2%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Informatica PowerCenter5.3%
Spring Cloud Data Flow1.2%
Other93.5%
Data Integration
 

Featured Reviews

Garima Goel - PeerSpot reviewer
Has supported complex data pipeline creation but performance tuning and monitoring responsiveness need improvement
Sometimes, I see various performance issues with Informatica PowerCenter, including caching concerns, whether it's a joiner transformation or other transformations, so I believe the team can enhance the performance perspectives of these transformations. Additionally, sometimes the Informatica Monitor hangs or takes time to open the current run or logs, which the team can also look into. Informatica is transitioning to cloud solutions and discontinuing on-premise support after 2026, so when we discuss Informatica Cloud and its support, it becomes quite expensive for the organization compared to peers such as SnapLogic or Netezza, which offer lower pricing. Informatica Cloud Intelligence's pricing is notably high.
NitinGoyal - PeerSpot reviewer
Has a plug-and-play model and provides good robustness and scalability
The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"It is an excellent ETL tool."
"Informatica PowerCenter is very good for integrating a huge amount of data in a very short duration, such as a minute. It is also very easy to use. After you provide the source and the target, mappings are automatically done, which makes it easy to use for the development team."
"Complex transformations can be easily achieved by using PowerCenter. The processing layer does transformations and other things. About 80% of my transformations can be achieved by using the middle layer. For the remaining 15% to 20% transformations, I can go in and create stored procedures in the respective databases. Mapplets is the feature through which we can reuse transformations across pipelines. Transformations and caching are the key features that we have been using frequently. Informatica PowerCenter is one of the best solutions or products in the data integration space. We have extensively used PowerCenter for integration purposes. We usually look at the best bridge solution in our architecture so that it can sustain for maybe a couple of years. Usually, we go with the solution that fits best and has proven and time-tested technology."
"We use Informatica PowerCenter to transfer the transitional database to and from the data warehouse. This is very efficient as it enables us to quickly find our data reports and the data, so we can build AI models."
"We can scale the product."
"It's a very powerful tool you can use to load data, get data, do the drawing between the tables, and put into the packet in a very fast way."
"Deployment was simple and straightforward."
"It's very easy to use it to develop mappings and workflows."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"The product is very user-friendly."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."
"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."
"The most valuable feature is real-time streaming."
"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."
 

Cons

"We had stability issues, mostly with JVM size."
"Informatica PowerCenter could improve on the documentation for the implementation. The documents provided are not very good for a new user."
"I would like to see an improvement in the digital adoption."
"Informatica, in my opinion, is very rigid and not very flexible, whereas platforms like Alteryx or Matillion are very flexible and agile."
"This solution needs the functionality to do batch processing of data. It also lacks connectivity to NoSQL, unstructured data sources."
"PowerCenter could be improved by having more big data components. Normally, we prefer Informatica as a relational database, but nowadays, companies are trying to understand and use big data components. I think it would be useful if we had more chances to create a hub ecosystem because customers try to use some data integration tasks by SQL, Spark and Spark codes, and Scala, but at the end of the day, the company will understand that we need to trace all the steps. An ETL tool is a must for that company, if we're talking about the regulated industries like finance, telcos, etc. If Informatica's biggest ecosystems feature were okay, I would prefer to use it."
"The documentation could be improved."
"The solution does not scale."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."
"The solution's community support could be improved."
"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"I would improve the dashboard features as they are not very user-friendly."
 

Pricing and Cost Advice

"The license model is CPU based."
"The pricing is a little expensive, but in the same range as IBM and other competitors."
"Licensing is a one time cost. But maintenance costs depend on what you want, how long you need it. Maintenance is a kind of insurance. With health insurance, you don't know whether you will get sick or need to go to hospital or not but you have to have insurance. It's the same thing with support. If you have that expertise in resolving issues, if you have enough experience in your IT department, I would say you don't need the support. But in practice, they recommend you go with the support. If you want support you have to pay for it."
"I consider this to be an expensive product."
"We are satisfied with the pricing."
"Our customers pay a licensing fee yearly."
"We have found the pricing very cost-effective. The licensing is CPU and data source-based."
"A basic setup can be from $100,000 and up annually."
"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."
"The solution provides value for money, and we are currently using its community edition."
"This is an open-source product that can be used free of charge."
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Comparison Review

it_user90069 - PeerSpot reviewer
Feb 20, 2014
Informatica PowerCenter vs. Microsoft SSIS - each technology has its advantages but also have similarities
Technology has made it easier for businesses to organize and manipulate data to get a clearer picture of what’s going on with their business. Notably, ETL tools have made managing huge amounts of data significantly easier and faster, boosting many organizations’ business intelligence operations…
 

Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
10%
Manufacturing Company
7%
Insurance Company
7%
Financial Services Firm
24%
Computer Software Company
14%
Retailer
8%
Manufacturing Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business15
Midsize Enterprise10
Large Enterprise72
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
 

Questions from the Community

How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
Which is better - SSIS or Informatica PowerCenter?
SSIS PowerPack is a group of drag and drop connectors for Microsoft SQL Server Integration Services, commonly called SSIS. The collection helps organizations boost productivity with code-free compo...
Which Informatica product would you choose - PowerCenter or Cloud Data Integration?
Complex transformations can easily be achieved using PowerCenter, which has all the features and tools to establish a real data governance strategy. Additionally, PowerCenter is able to manage huge...
What needs improvement with Spring Cloud Data Flow?
There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...
What is your primary use case for Spring Cloud Data Flow?
We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...
What advice do you have for others considering Spring Cloud Data Flow?
I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...
 

Also Known As

PowerCenter
No data available
 

Overview

 

Sample Customers

University of Texas MD Anderson Cancer Center, LexisNexis, Rabobank
Information Not Available
Find out what your peers are saying about Informatica PowerCenter vs. Spring Cloud Data Flow and other solutions. Updated: November 2025.
872,869 professionals have used our research since 2012.