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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) (6th), Business-to-Business Middleware (3rd), API Management (7th), 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
22nd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of February 2025, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 5.0%, down from 7.8% 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

"It has all the advantages of the Cloud in that you can use it without worrying about infrastructure, upkeep, or upgrades."
"I like EDC's self-service capabilities. You can put the catalog on the intranet inside the organization, so users can search for something. People in the research world have specialized systems, and you might find data from various places that sound similar."
"I am impressed by the solution's interface."
"It is a scalable product."
"The OAuth feature is the most valuable feature for authentication."
"I give the stability a ten out of ten."
"The tool's most valuable feature is bulk upload. We upload files in CSV or Excel format."
"​The tool manually checks on applying business rules and helps to implement them."
"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."
"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."
"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 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."
 

Cons

"New machine learning could be added to Informatica MDM because the solution is outdated and is not moving with the current trends. The solution is good, but it definitely needs a lot of improvement and needs to speed up as per the market."
"Needs to implement the new workflow with simple steps and a quick visualization with a 360 view of the data."
"Though EDC has maximum coverage, a few things were not available to scan, but I think EDC is evolving to address this issue."
"The initial setup was not very straightforward. Not complex, but not very simple either."
"Their support should be improved. We have had some trouble with their support from time to time. Its scalability should also be improved. I would also like to have a bit more modern and friendly UI for the end-users. There should definitely be a simplified way to configure and set it up."
"The user interface can be a bit more functionality-aligned."
"There is room for improvement in the support. The response time could be faster."
"Informatica MDM can improve the data catalog and data marketplace."
"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."
"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."
"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."
"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."
 

Pricing and Cost Advice

"The product is not very pocket-friendly for small and medium-sized businesses, and it is understandable because of the kind of features the tool gives."
"You can purchase licenses for this solution at different intervals. For example, annually or every three years. They recently changed their terms for licensing and now it is more flexible."
"It is cost effective and an easily accessible tool."
"The price of Informatica Cloud Data Integration could be reduced."
"It's an expensive solution."
"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."
"Informatica MDM is very expensive. Apart from licensing fees, they have broken down their products into multiple products, and they charge for each and every product. If the data is huge, they charge for the data. At times, we have to use third party services for data cleaning, and they charge for that as well."
"It's a very expensive solution"
"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."
"The solution provides value for money, and we are currently using its community edition."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
12%
Manufacturing Company
10%
Government
6%
Financial Services Firm
25%
Computer Software Company
18%
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: January 2025.
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