Try our new research platform with insights from 80,000+ expert users

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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
183
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (13th), Business-to-Business Middleware (4th), 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
22nd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 4.4%, down from 7.2% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, 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 tool's most valuable feature is bulk upload. We upload files in CSV or Excel format."
"We use parts and standardization for most of our testing. We purchase the US Postal Service address database, which is updated periodically. Many useful tools, such as Google Maps, can detect and mark new businesses or changes in business locations. Informatica captures and updates this information. Some periodic maintenance is involved, but setting it up is not overly complicated."
"The user interface which is very easy to use if we have any problems to solve."
"The interface has a great look and feel, and the functionality is so easy."
"The features that I have found most valuable are, first of all, that it comes as part of this whole bundle of Informatica tools. So if you've been implementing Informatica MDM across a business, you'd often find it comes with it. It's been thrown in as a sweetener. The adoption of it is often the challenge because as part of your MDM project, governance is seen as something beyond the MDM and is often restrictive. So this tool actually, for the first time, when you talk to data governance teams, gives a holistic view of what a data governance team can do with this tool."
"It is quite easy to use and flexible."
"The most valuable feature is the building of mockups and tasks."
"The solution is stable."
"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 product is very user-friendly."
"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 most valuable feature is real-time streaming."
"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 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 dashboards in Spring Cloud Dataflow are quite valuable."
 

Cons

"The configurations could be better. It is a bit confusing because we must develop two tools when building a data model in Informatica MDM. Even though Informatica MDM is a single tool, we have our hub console plus the provisioning tool within that. Whatever data model we are building in the hub console, we have to develop it in the provisioning tool again. It is double the work to create a data model. We are also using external calls or the Java custom plans functions. This can be both positive and negative. Since MDM as a client does not support any complex validation, we have to depend on the external call or a Java call. Every time we deployed, the entire solution was impacted if something went wrong."
"It could be a bit more intuitive, rather than technically complex."
"It is not easy to set up and configure the tool."
"I would like to have the solution in one product and technical support needs to be better."
"Informatica's support understands the solution, but they lack the experience we need for our use case. That was one thing that we prioritized when we started searching for this kind of solution."
"They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently."
"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."
"There are a small number of UI bugs that occur on occasion."
"The solution's community support could be improved."
"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 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."
"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."
"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."
 

Pricing and Cost Advice

"Informatica MDM's pricing is not cheap but comparable to other vendors."
"It's offers value for money. They're more competitive with respect to pricing and offerings."
"Informatica Axon is a costly solution. I rate Informatica Axon a four out of ten for its pricing."
"Pricing is determined by the number of licensed users as well as the number of Core CPUs."
"I rate Informatica MDM's price a six on a scale of one to ten, where one is a low price, and ten is a high price."
"The licensing price of the product depends on the organization's requirements."
"The solution's pricing model is easy, but it is very expensive."
"It is cost effective and an easily accessible tool."
"This is an open-source product that can be used free of charge."
"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."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
851,604 professionals have used our research since 2012.
 

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
18%
Retailer
7%
Manufacturing Company
5%
 

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: April 2025.
851,604 professionals have used our research since 2012.