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Informatica Intelligent Data Management Cloud (IDMC) vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 11, 2025

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 Intelligent Dat...
Ranking in Data Integration
2nd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
214
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (6th), Business-to-Business Middleware (3rd), API Management (7th), Cloud Data Integration (3rd), Data Governance (3rd), Test Data Management (3rd), Cloud Master Data Management (MDM) (1st), Data Management Platforms (DMP) (2nd), Data Masking (1st), Metadata Management (1st), Integration Platform as a Service (iPaaS) (3rd), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (1st), AI Data Analysis (1st)
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 December 2025, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 3.9%, down from 5.8% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, 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 Intelligent Data Management Cloud (IDMC)3.9%
Spring Cloud Data Flow1.1%
Other95.0%
Data Integration
 

Featured Reviews

Divya-Raj - PeerSpot reviewer
Sr. Consultant cum Assistant Manager & Offshore Lead at Deloitte
Handles large data volumes effectively and offers competitive pricing
There is a lot of improvement required, as we still face some cache issues most of the time, which is a challenge that we expect to see resolved in the future. Additionally, there is some limitation when we are working with a tool, especially regarding In and Out parameters, and I feel that this aspect should be improved going ahead. We face issues with the API side, as Cloud Application Integration cannot handle large volumes; according to the API page, there is a limitation of 500 records or 500 MB. The AI integrated into the Informatica Intelligent Cloud Services solution is called Application Integration, where we still face challenges when dealing with huge volumes, as previously explained.
LN
Senior Software Engineer at QBE Regional Insurance
Provides ease of integration with other cloud platforms
Spring Cloud Data Flow is a useful product if I consider how there are different providers with whom my company had to deal, and most of them offer cloud-based products. I can't explain any crucial circumstances where the product's integration capabilities were helpful, but the aforementioned details explain the scenario for which I used the solution. I was only involved with the development of the product and not with the data pipeline configuration phase. The use of Spring Cloud Data Flow greatly impacted projects' time to market since our company's intention was to actually deploy and ensure that the payment platform integrated with it, which was an easy process. The product's user interface was very intuitive. The tool was deployed in multiple environments, but I am not sure about the production. From the time I started taking up the job in my current organization, I saw that we have deployed the tool in multiple environments wherein the number of users extensively used the product in the UAT environment, which is one of the most stable environments. There were 20 different methods to test the tool. I wouldn't be able to tell you the production details of the tool as I was more part of the production deployment, but I can say that it was deployed with the intent of making it available for 10,000 users. Those who plan to use the product should enjoy the flexibility of the solution. I rate the tool a nine out of ten.

Quotes from Members

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

Pros

"There isn't any human touch involved. It's just an automated business process to build different applications and talking to various APIs using the client's ecosystems. We then build new functionalities out of it."
"It has been leading the market with hierarchy management and all the different match concepts and algorithms. They're very robust."
"The product seems stable enough."
"The solution has the best feature for parameterization."
"Informatica Data Quality is a product that is worth the money."
"The solution is applicable for both technical and business users."
"Axon does one interesting thing that I don't think other tools do as well. It lets you rate data and incorporates Informatica's data quality feature into it. There are little indications and graphics that show you how good the data quality is, and you can drill into it to see where potential issues lie."
"I rate the technical support a ten out of ten."
"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."
"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 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 dashboards in Spring Cloud Dataflow are quite valuable."
"The most valuable feature is real-time streaming."
"The product is very user-friendly."
"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

"I would like to see support for more data sources."
"The integration with other data management tools can be enhanced. For instance, there is no integration with tools like Collibra or Hubview."
"I feel the out-of-the-box APIs or the API management could be improved slightly from their current state. It could be more user-friendly."
"The product could be improved in the area of architecture and technology. All the parts are old."
"The integration could be a bit better. The process is something new."
"Needs to implement the new workflow with simple steps and a quick visualization with a 360 view of the data."
"The integration process is not easy."
"Support response time could be better."
"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."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"Spring Cloud Data Flow is not an easy-to-use tool, so 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 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."
"I would improve the dashboard features as they are not very user-friendly."
"The solution's community support could be improved."
 

Pricing and Cost Advice

"The pricing is quite flexible."
"The price of Informatica Cloud Data Integration could be reduced."
"It's an expensive solution."
"In terms of the licensing for Informatica Intelligent Cloud Services, we had the option of paying based on the number of users and paying based on the volume of data, and we went with the data volume licensing option. Informatica Intelligent Cloud Services isn't as expensive as CIG. The pricing for it is okay, so I'm rating it a four out of five in terms of pricing. We did use the email verification and address validation services which weren't part of the contract, so we had to pay additional fees for those services."
"The licenses attached to the solution are highly priced."
"We got a 50% discount."
"There is no doubt that it is very expensive, but the brand value comes at a cost. Other MDM solutions in the market that haven't proven themselves like Informatica are also pretty expensive. We need to understand that MDM itself is very expensive to implement. So, Informatica is also pretty expensive. I would rate it a two out of five for being pretty expensive."
"I have no idea what the price actually is. It is probably not going to be the cheapest, but it is a pretty stable and robust platform from the backend standpoint."
"This is an open-source product that can be used free of charge."
"The solution provides value for money, and we are currently using its community edition."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
10%
Computer Software Company
9%
Retailer
7%
Financial Services Firm
22%
Computer Software Company
13%
Retailer
8%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business51
Midsize Enterprise27
Large Enterprise153
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
 

Questions from the Community

How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
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 are the biggest benefits of using Informatica Cloud Data Integration?
When it comes to cloud data integration, this solution can provide you with multiple benefits, including: Overhead reduction by integrating data on any cloud in various ways Effective integration ...
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

ActiveVOS, Active Endpoints, Address Verification, Persistent Data Masking
No data available
 

Overview

 

Sample Customers

The Travel Company, Carbonite
Information Not Available
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879,259 professionals have used our research since 2012.