IBM Cloud Pak for Data vs Spring Cloud Data Flow comparison

IBM and Broadcom are both solutions in the Data Integration category. IBM is ranked #26 with an average rating of 7.0, while Broadcom is ranked #21 with an average rating of 7.8. IBM holds a 1.8% mindshare in DI, compared to Broadcom’s 1.2% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

2,186 Views
2,055 Comparison Views

86% 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

IBM Cloud Pak for Data

Spring Cloud Data Flow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Spring Cloud Data Flow and IBM Cloud Pak for Data are competing in the cloud data management and orchestration market. IBM Cloud Pak for Data appears to have the upper hand owing to its comprehensive features.

Features: Spring Cloud Data Flow is recognized for real-time stream processing, batch workloads, and ease of integration with third-party applications. It provides seamless handling of microservices. IBM Cloud Pak for Data offers a wide range of data management tools, advanced AI and machine learning capabilities, and robust data governance features.

Room for Improvement: Spring Cloud Data Flow could enhance its range of data management tools and improve AI capabilities. Its data governance features could also be more robust. IBM Cloud Pak for Data might simplify its deployment process and improve cost-effectiveness. It could offer a more straightforward integration process.

Ease of Deployment and Customer Service: Spring Cloud Data Flow is praised for its straightforward deployment and responsive customer support team. IBM Cloud Pak for Data's deployment is more complex due to its extensive features, but it offers comprehensive documentation and robust support to facilitate integration.

Pricing and ROI: Spring Cloud Data Flow is noted for cost-effectiveness, leading to quicker ROI. Although IBM Cloud Pak for Data requires a higher initial investment, it provides significant ROI with long-term efficiencies and advanced capabilities.

To learn more, read our detailed IBM Cloud Pak for Data vs. Spring Cloud Data Flow Report (Updated: September 2025).

Buyer's Guide

IBM Cloud Pak for Data vs. Spring Cloud Data Flow

September 2025

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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

IBM Cloud Pak for Data

Ranking in Data Integration

26th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

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 IBM Cloud Pak for Data is 1.8%, up from 1.7% 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%
IBM Cloud Pak for Data	1.8%
Other	97.0%

Data Integration

Featured Reviews

Michelle Leslie

Data asset management engineer at a tech services company with 1-10 employees

Starts strong with data management capabilities but needs a demo database

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

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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

"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."

"Cloud Pak is a very, very, very good system."

"IBM Watson Catalog and data pipelines are the most valuable features of the solution."

"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."

"You can model the data there, connect the data models with the business processes and create data lineage processes."

"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."

"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."

"Its data preparation capabilities are highly valuable."

More IBM Cloud Pak for Data pros

"The most valuable feature is real-time streaming."

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

"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."

"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 dashboards in Spring Cloud Dataflow are quite valuable."

"The product is very user-friendly."

"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

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

"The solution could have more connectors."

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

"The product must improve its performance."

"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."

"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."

"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."

"What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated."

More IBM Cloud Pak for Data cons

"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."

"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 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."

Pricing and Cost Advice

"It's quite expensive."

"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."

"The solution's pricing is competitive with that of other vendors."

"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."

"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."

"I think that this product is too expensive for smaller companies."

"The solution is expensive."

"Cloud Pak's cost is a little high."

"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."

"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

28%

Manufacturing Company

10%

Computer Software Company

Government

Financial Services Firm

24%

Computer Software Company

15%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	7
Large Enterprise	8

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

Questions from the Community

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

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What needs improvement with IBM Cloud Pak for Data?

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What is your primary use case for IBM Cloud Pak for Data?

My primary use case for Cloud Pak is that I am the reference Data steward for the Africa regions in the banks where I work. My main objective is to capture the reference data in Caltech or Data and...

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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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Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 44% of the time

Denodo vs IBM Cloud Pak for Data

Compared 13% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM Cloud Pak for Data

Compared 11% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 9% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 8% of the time

More IBM Cloud Pak for Data Competitors

Apache Flink vs Spring Cloud Data Flow

Compared 39% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 9% of the time

MuleSoft Anypoint Platform vs Spring Cloud Data Flow

Compared 6% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 5% of the time

Google Cloud Dataflow vs Spring Cloud Data Flow

Compared 5% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

October 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

Spring Cloud Data Flow

September 2025

Download Spring Cloud Data Flow product report

Also Known As

Cloud Pak for Data

No data available

Overview

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

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

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Information Not Available

Buyer's Guide

IBM Cloud Pak for Data vs. Spring Cloud Data Flow

September 2025

Free Report: IBM Cloud Pak for Data vs. Spring Cloud Data Flow

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