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Informatica Intelligent Data Management Cloud (IDMC) 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 Intelligent Dat...
Ranking in Data Integration
2nd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
185
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (11th), Business-to-Business Middleware (5th), API Management (8th), Cloud Data Integration (3rd), Data Governance (2nd), Test Data Management (3rd), Cloud Master Data Management (MDM) Solutions (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (1st), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd)
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 (9th)
 

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 4.3%, down from 7.0% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.2%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Raj Sethupathi - PeerSpot reviewer
Offers profiling and address standardization but can be complicated
Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data. The cleansed version of the data is stored in the data warehouse. It integrates with PowerCenter and other Informatica tools. The integration details can be complex, but a regional setup is involved in this process. Profiling smaller datasets, such as 10,000-50,000 records, worked fine. However, unexpected issues could arise with larger datasets, such as thousands of records or more, especially with tables containing many columns. Handling tables with fifty or more columns can be challenging, even in Excel. A mismatch in data types could cause the entire system to crash. Continual enhancements are being made to address these issues, which can be unique to specific industries like finance and healthcare.
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

"The serverless capability and the packaging application of the solution are valuable."
"What I like best about Informatica MDM is its structured, table-based approach. Unlike Reltio, where data is only visible through the UI and cloud-based, the solution allows access to normalized tables. This means I can directly query and see data in each table. For instance, I can easily get all customer details from the customer table. However, for more complex queries, like seeing all customer interactions with the organization, some SQL knowledge is needed to join different tables and retrieve the details."
"The solution's initial setup is quite straightforward."
"I am impressed by the solution's interface."
"The application integration will give you more flexibility when dealing with APIs."
"The data mapping capability is a valuable feature."
"The most valuable feature is data discovery. This is the most exciting feature for all of the banks."
"It provides all the typical MDM capabilities like deduplication and machine survivorship."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"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 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 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."
"The most valuable feature is real-time streaming."
"The product is very user-friendly."
"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"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."
 

Cons

"Right now, although they offer some templates, I would want more templates available to be imported."
"One area that needs to improve is the user experience because it is very complex. The trial version is very complex so it's not easy to start using the program immediately. You must study the rules first."
"Informatica Cloud Data Integration can improve by being more user-friendly. When you're working with the solution a lot of technical knowledge is required. It's not a solution that anyone can use properly, you need knowledge of what's happening at the back end, such as SQL. When you get stuck, you need to look into your logic. For other tools, such as Dell Boomi, anyone can use them."
"The initial setup was not very straightforward. Not complex, but not very simple either."
"There is room for improvement in the Data Marketplace aspect."
"There's no direct way to connect to Amazon APIs from Informatica Cloud."
"The integration could be a bit better. The process is something new."
"The biggest pain point for us is the documentation. Typically, you have to go through knowledge forums and knowledge groups to find out about the syntax issues for interfacing with new products. Typically, you've got to deal with someone who has been through the pain before. Their documents are not really up to date with current innovations happening in the industry. As big as they are, you can't really expect it, but that's our pain point."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"The solution's community support could be improved."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"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."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"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."
"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."
 

Pricing and Cost Advice

"Informatica Cloud Data Integration is famously known for its high price. The vendor targets large enterprises, and not medium or small companies. These large companies, and organizations, handle large amounts of data. If you go into any large bank, such as American or Canadian banks, these banks use this solution because it is more reliable, secure, and has more functionality."
"Our customers sometimes are able to negotiate a much better price for Informatica Cloud Data Integration based on their relationship with the vendor."
"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."
"The price of Informatica Cloud Data Integration could be reduced."
"it's expensive, but if you're looking for a stable solution, Informatica MDM is a good one to choose."
"Informatica Axon is a costly solution. I rate Informatica Axon a four out of ten for its pricing."
"The pricing is quite flexible."
"The price is very high and has become a big concern for our customers who require the solution in order for their business to function smoothly."
"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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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
12%
Manufacturing Company
9%
Insurance Company
6%
Financial Services Firm
26%
Computer Software Company
17%
Retailer
7%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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, BPM, Address Verification, Persistent Data Masking, Cloud Test Data Management, PIM, , Enterprise Data Catalog, Data Integration Hub, Cloud Data Integration, Data Quality, Cloud API and App Integration
No data available
 

Overview

 

Sample Customers

The Travel Company, Carbonite
Information Not Available
Find out what your peers are saying about Informatica Intelligent Data Management Cloud (IDMC) vs. Spring Cloud Data Flow and other solutions. Updated: June 2025.
856,873 professionals have used our research since 2012.