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Informatica Intelligent Data Management Cloud (IDMC) vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Informatica Intelligent Dat...
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
181
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (7th), 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) (2nd), Data Masking (2nd), Metadata Management (1st), Test Data Management Services (4th), Product Information Management (PIM) (1st), Data Observability (2nd)
Spring Cloud Data Flow
Ranking in Data Integration
22nd
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
9
Ranking in other categories
Streaming Analytics (10th)
 

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 a more UI-based tool, and the scripting is good."
"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."
"The features I find most valuable is the synchronization, verification, functionalities and all the data integration features."
"The capability of the tool to scan and capture the metadata from a variety of sources is one of the capabilities that I find most useful. The central repository into which it is going to put that captured metadata is the best."
"The solution is applicable for both technical and business users."
"Informatica Cloud Data Integration is stable."
"Multifeatured and easily scalable data catalog, with good data domain discovery and data profiling features."
"I am impressed by the solution's interface."
"The product is very user-friendly."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"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."
"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 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

"It needs to be a little more intuitive but it’s really not bad."
"I would like to see support for more data sources."
"Some functionalities can be a challenge in the cloud."
"We would like to have accessibility to the repository."
"I would like to see better visuals for business users, such as a dashboard where they can precisely track where problems are."
"The tool could be improved in terms of ease of use, particularly for those without technical expertise. Understanding and extracting data from the table-based structure requires some SQL knowledge and technical skills. Additionally, while Informatica MDM has moved towards a cloud-based MDM with a UI similar to Reltio, I haven't used it, so I can't comment on its effectiveness."
"It would be helpful if there was a GenAI feature integrated into the system, especially regarding the data quality."
"There may be some types of limitations with the performance."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"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."
"I would improve the dashboard features as they are not very user-friendly."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"Spring Cloud Data Flow is not an easy-to-use tool, so 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."
 

Pricing and Cost Advice

"On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing nine and a half out of ten."
"I rate the product's price a seven on a scale of one to ten, where one is the cheapest and ten is the most expensive. The product is a bit expensive."
"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."
"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."
"The solution's pricing model is easy, but it is very expensive."
"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."
"I have heard from customers that the product comes with a huge license cost."
"The price is comparable."
"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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
10%
Insurance Company
6%
Financial Services Firm
29%
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?
I would improve the dashboard features as they are not very user-friendly. Another area for improvement is the documentation, as it is not very precise. There are limited resources available on Spr...
What is your primary use case for Spring Cloud Data Flow?
I am a developer using Spring Cloud Dataflow. We primarily use it to convert our applications from monolithic to microservices. The solution is used for scheduling tasks in a specific order and ens...
What advice do you have for others considering Spring Cloud Data Flow?
My advice would be to thoroughly review the documentation and understand if Spring Cloud Dataflow is the right solution for your application. For applications with only one or two microservices, it...
 

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
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Find out what your peers are saying about Informatica Intelligent Data Management Cloud (IDMC) vs. Spring Cloud Data Flow and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.