Informatica Enterprise Data Lake vs Spring Cloud Data Flow comparison

Informatica and Broadcom are both solutions in the Data Integration category. Informatica is ranked #39 with an average rating of 8.0, while Broadcom is ranked #21 with an average rating of 7.8. Informatica holds a 0.4% mindshare in DI, compared to Broadcom’s 1.2% mindshare. Additionally, 100% of Informatica users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Informatica Enterprise Data...

Read 2 Informatica Enterprise Data Lake reviews

467 Views
360 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,001 Views
1,230 Comparison Views

88% willing to recommend

Informatica Enterprise Data...

Spring Cloud Data Flow

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Executive Summary

We performed a comparison between Informatica Enterprise Data Lake and Spring Cloud Data Flow based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Informatica Enterprise Data Lake vs. Spring Cloud Data Flow Report (Updated: October 2025).

Buyer's Guide

Informatica Enterprise Data Lake vs. Spring Cloud Data Flow

October 2025

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Helped 869,760 peers since 2012

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 Enterprise Data...

Ranking in Data Integration

39th

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

21st

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (10th)

Mindshare comparison

As of October 2025, in the Data Integration category, the mindshare of Informatica Enterprise Data Lake is 0.4%, up from 0.2% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.2%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Spring Cloud Data Flow	1.2%
Informatica Enterprise Data Lake	0.4%
Other	98.4%

Data Integration

Featured Reviews

Santanu Bhattacharya

Technical manager at Cognizant

Have built an enterprise-level cloud data pipeline with reliable governance and integration

People use Informatica Enterprise Data Lake because we can create the whole journey from data migration projects from the legacy system to AWS and to the Lake architecture, covering the entire journey from the source to the landing zone, then to the curated zone, and finally consumed by both downstream and upstream applications. The main benefit of Informatica Enterprise Data Lake is that it allows you to use different types of data types, including blobs and storage; all types of data—structured, unstructured, and semi-structured—can exist in the Data Lake architecture, making it robust for retrieving data based on your filtration needs. Its value is actually governed by the client, who combined with our company and AWS, so we all work together to use the workspace and all these things for Informatica Enterprise Data Lake.

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Alokik Gupta

Software Engineer at Tech Mahindra Limited

Effective microservice and task management but needs more dashboard features

The dashboards in Spring Cloud Dataflow are quite valuable. By injecting the dependency of Spring Cloud Dataflow into our Spring Boot application and annotating it with 'enable task annotation', we can manage tasks effectively. Additionally, the platform allows us to create pipelines and use microservices like a logical AND gate, giving us greater control over our microservices.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The process of using the tool's scalability option is well documented."

"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 product is very user-friendly."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

"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 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 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

"Informatica Enterprise Data Lake's setup process was complex since it doesn't support a lot of real-time systems."

"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."

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

"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."

"The solution's community support could be improved."

Pricing and Cost Advice

"The licenses attached to the solution are highly priced."

"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

No data available

Financial Services Firm

24%

Computer Software Company

15%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	5

Questions from the Community

What do you like most about Informatica Enterprise Data Lake?

The process of using the tool's scalability option is well documented.

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What is your experience regarding pricing and costs for Informatica Enterprise Data Lake?

Informatica Enterprise Data Lake's cost is higher, but it provides good value for the price. It comes at a reasonable price, which I would rate at eight out of ten.

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What needs improvement with Informatica Enterprise Data Lake?

Improvement depends upon how we can faster showcase our data in our reports, whether in Power BI, Tableau, or other formats. Improving the speed of data showcasing and filtration would be better, a...

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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...

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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...

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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...

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Product Reports

Buyer's Guide

Data Integration

September 2025

Download Informatica Enterprise Data Lake product report

Buyer's Guide

Spring Cloud Data Flow

September 2025

Download Spring Cloud Data Flow product report

Also Known As

Informatica Intelligent Data Lake, Intelligent Data Lake

No data available

Overview

The Intelligent Data Lake enables raw big data to be systematically transformed into fit-for-purpose data sets for a variety of data consumers. Data scientists and analysts can quickly find the data they’re looking for using semantic and faceted search. They can see data profiles, lineage, and other relationships to know whether they can trust the data and whether it’s fit-for-use in their analytic projects.

Informatica

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

Broadcom

Buyer's Guide

Informatica Enterprise Data Lake vs. Spring Cloud Data Flow

October 2025

Free Report: Informatica Enterprise Data Lake vs. Spring Cloud Data Flow

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