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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
3rd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
182
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (11th), 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) (1st), Data Masking (2nd), Metadata Management (1st), Test Data Management Services (2nd), Product Information Management (PIM) (1st), Data Observability (2nd)
Spring Cloud Data Flow
Ranking in Data Integration
23rd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of March 2025, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 4.8%, down from 7.7% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.8% 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

"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."
"New tools are coming out that will enable you to achieve 90 percent of use cases with the out-of-the-box configuration, but I would like to keep Informatica tight here. Otherwise, you need a Java user edit course and other things to do multiple things that you cannot configure out of the box. They have to go through those use cases to do something if those can also be configured rather than coded."
"I like the number of options that are presented with Informatica, fuzzy matching, and your screen."
"The tool's most valuable feature is bulk upload. We upload files in CSV or Excel format."
"I have rated the stability a ten out of ten due to a high level of satisfaction."
"The ability to aggregate and put together data from around fifty sources into one environment allows us to have a preview of everything in a single place, which is something we did not have previously in our company."
"I think the integration feature is probably one of the key features in Informatica MDM...Stability-wise, I rate the solution a ten out of ten."
"The most important features are the mastering of the data and the UI intuitiveness."
"The product is very user-friendly."
"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."
"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 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 dashboards in Spring Cloud Dataflow are quite valuable."
 

Cons

"The on-prem solution is harder to learn than the cloud-based versions."
"Permissions, scalability, and connection with other informatic tools are the main areas that need development. Integration with other tools, such as IDQ, is challenging. The management of data discovery is highly challenging because many data points have identical definitions."
"The integration could be a bit better. The process is something new."
"The cloud version of the Informatica, it's a very substandard product. They might say it's enterprise-ready but it's not at all ready. They need to add more features, such as improved data replication features. If you look at other tools, such as Matillion they are now cloud-native and flexible. Additionally, Informatica Cloud Data Integration should have a good migration strategy from Informatica PowerCenter to Informatica Cloud Data Integration."
"One area that could use improvement is the speed of the web interfaces. At present, they are very slow. I think it is essential that we are original and robust on-premises."
"Informatica MDM could improve the interdependency with integration. The solution sometimes becomes a bit difficult to change considering a lot of interdependency with the integration. There can be some improvement in the workflows and they can introduce more artificial intelligence."
"Managing the licenses with the on-premises version was difficult."
"Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data."
"I would improve the dashboard features as they are not very user-friendly."
"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."
"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."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"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."
 

Pricing and Cost Advice

"Informatica MDM's pricing is not cheap but comparable to other vendors."
"A yearly subscription is paid based on the number of people using the solution. Price-wise, it falls under the medium range since it is neither very costly nor too cheap."
"Cost-wise, I think it is on the higher side, and that is why we are looking for some better options. Licensing costs are huge compared to other players in the market and for my company."
"Informatica Axon is a costly solution. I rate Informatica Axon a four out of ten for its pricing."
"I have heard from customers that the product comes with a huge license cost."
"The product is highly-priced."
"We are quite happy with the licensing model."
"We saw an ROI. We have been able to get data from various sources and consolidate it into a data lake, which is helping us in data analytics."
"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."
"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
10%
Insurance Company
6%
Financial Services Firm
25%
Computer Software Company
17%
Manufacturing Company
7%
Retailer
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: March 2025.
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