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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) (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) (1st), 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
24th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 4.6%, down from 7.5% 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

"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."
"The user interface which is very easy to use if we have any problems to solve."
"The most valuable feature of Informatica Enterprise Data Catalog is it provides clients with a full view of the enterprise data assets. For example, how many data assets they have and who owns them."
"Able to customize data search and data sharing."
"The product is stable."
"Replication allows us to fully replicate all objects from Shop Floor Data Collection (SFDC) to in-house/on-premises database in one job."
"We can see all our information on a single screen."
"The most valuable features are the structure masking and platform masking."
"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 best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"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 most valuable feature is real-time streaming."
"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 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."
 

Cons

"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."
"It is complicated to establish the lineage in EDC using PowerCenter mappings."
"The product interface could be improved to be more intuitive."
"The regions in which the data resides are still limited. This could be an issue in terms of the data residency laws of some of the countries. They should get more regions."
"The main issue preventing Brazilian companies from migrating to Informatica Cloud Data Integration from on-prem is the price."
"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."
"They have to improve their relationship discovery tool. They say that they have AI inside, but this AI did not automatically find relationships or suggested relationships between entities."
"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 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."
"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."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"The solution's community support could be improved."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
 

Pricing and Cost Advice

"We have licenses, and we are provided with certain particular services in the solution."
"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."
"It's a costly solution"
"It's pretty high for us. It's more on the higher side, like low to middle high."
"The price is neither too high nor too low."
"The solution is very expensive."
"It is expensive. That's probably the biggest drawback. The business has heartache paying the license, but that's mainly because they don't realize what value it brings. The key thing about the MDM solution is that it is in the backend, and no one sees what it is actually doing. You don't know it is a problem until it is not there."
"We are quite happy with the licensing model."
"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
10%
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
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