IBM InfoSphere DataStage vs Spring Cloud Data Flow comparison

IBM and VMware are both solutions in the Data Integration category. IBM is ranked #6 with an average rating of 8.0, while VMware is ranked #21 with an average rating of 7.8. IBM holds a 4.8% mindshare in DI, compared to VMware’s 1.2% mindshare. Additionally, 83% of IBM users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

IBM InfoSphere DataStage

Read 42 IBM InfoSphere DataStage reviews

7,117 Views
6,049 Comparison Views

83% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,372 Views
1,281 Comparison Views

88% willing to recommend

IBM InfoSphere DataStage

Spring Cloud Data Flow

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Executive SummaryUpdated on Dec 19, 2024

IBM InfoSphere DataStage and Spring Cloud Data Flow are prominent contenders in the field of data integration and orchestration platforms. DataStage generally appears more feature-rich with extensive ETL capabilities, but Spring Cloud Data Flow offers flexibility and cost-effectiveness.

Features: IBM InfoSphere DataStage is known for robust ETL capabilities, parallel processing, and comprehensive metadata management. It supports high scalability and seamless integration with other IBM products. Spring Cloud Data Flow is distinguished by its simple programming model and microservices orchestration. It enables real-time streaming and integrates seamlessly into cloud environments such as Kubernetes. It also provides a flexible plug-and-play model for creating automated workflows.

Room for Improvement: IBM InfoSphere DataStage users suggest improvements in cost-effectiveness, cloud support, and performance monitoring. There's a need for a more intuitive interface and better integration with modern data sources. Spring Cloud Data Flow could benefit from enhancements in its user interface, better documentation, and stronger community support. Users face some technical challenges with configurations, needing more transparent guidance and support.

Ease of Deployment and Customer Service: IBM InfoSphere DataStage mainly supports on-premises deployments, with some hybrid capabilities. User feedback on IBM's technical support is mixed, varying by region and issue. Spring Cloud Data Flow supports on-premises and private cloud environments, with generally positive feedback on customer service, though improvements in handling variety could increase satisfaction.

Pricing and ROI: IBM InfoSphere DataStage is an expensive investment compared to other options. It incurs substantial costs for licenses and maintenance, presenting a high cost of ownership. Spring Cloud Data Flow, being open-source, offers a no-cost entry, and users typically find it more economically favorable with better ROI, considering its flexible usage and only incurring costs for support services.

To learn more, read our detailed IBM InfoSphere DataStage vs. Spring Cloud Data Flow Report (Updated: July 2025).

Buyer's Guide

IBM InfoSphere DataStage vs. Spring Cloud Data Flow

July 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 InfoSphere DataStage

Ranking in Data Integration

6th

Average Rating

7.8

Reviews Sentiment

6.8

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 (9th)

Mindshare comparison

As of July 2025, in the Data Integration category, the mindshare of IBM InfoSphere DataStage is 4.8%, down from 5.6% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.2%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Swetha S

Sr Product Manager at a computer software company with 501-1,000 employees

The solution streamlines design, development, and deployment with effective ETL features

The support has been really good. Typically, if we have any issues, we raise a ticket with IBM, and they help us resolve the issues if required. We also have the flexibility to submit a feature request to be included as part of the wishlist, potentially becoming a product feature in subsequent releases.

Read full review

NitinGoyal

Engineering Lead at Naukri.com

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.

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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

"It generates highly efficient backend code to write data onto IBM systems, which I find valuable."

"The product is easy to deploy."

"The most valuable feature is the data integration for data warehousing."

"I am impressed with the tool's ETL tracing."

"The concept of integration is a valuable feature of the product."

"The most valuable feature is the product's versatility to inject data."

"Finding logs is very easy on the solution."

"The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"

More IBM InfoSphere DataStage pros

"The product is very user-friendly."

"The dashboards in Spring Cloud Dataflow are quite valuable."

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

"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 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 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 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

"The interface needs work to be more user-friendly."

"Currently lacking virtualization ability."

"The initial setup can be complex."

"The deployment could be more straightforward."

"It would be great if they can include some basic version of data quality checking features."

"Working with some of the big data components is good, but I can see improvements are needed."

"The solution can be a bit more user-friendly, similar to Informatica."

"What needs improvement in IBM InfoSphere DataStage is its pricing. The pricing for the solution is higher than its competitors, so a lot of the clients my company has worked with prefer other tools over IBM InfoSphere DataStage because of the high price tag. Another area for improvement in the solution stems from a lot of new types of databases, for example, databases in the cloud and big data have become available, and IBM InfoSphere DataStage is working on various connectors for different data sources, but that still isn't up-to-date, meaning that some connectors are missing for modern data sources. The latest version of IBM InfoSphere DataStage also has a complex architecture, so my team faced frequent outages and that should be improved as well."

More IBM InfoSphere DataStage cons

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

"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 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."

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

"I would improve the dashboard features as they are not very user-friendly."

Pricing and Cost Advice

"Small and medium-sized companies cannot afford to pay for this solution."

"It's very expensive."

"Our internal team takes care of group licensing and cost. We don't have individual licenses. We have group licensing at the company level. Usually, IBM doesn't charge anything separately on the licensing side. For storage and everything else, we are paying around $6,000 per month, which is not very high. It includes Linux data storage, execution, and licensing. They're charging $40 for one-hour execution. Based on that, we are spending around $2,000 on the production environment and $1,000 on the lower environment for testing and development-side executions. For the mainframe, we are using the Db2 mainframe database, and we are spending around $1,000 on the Db2 mainframe database as well. All this comes out to be around $6,000. We, however, would like to have some cost reduction."

"The product is expensive."

"I have no information on the exact pricing for IBM InfoSphere DataStage because the solution is usually procured by the clients my company works with, though the pricing is higher compared to other solutions, so many clients choose to go with a different solution rather than IBM InfoSphere DataStage."

"High-cost of ownership: They could take a page from open source software."

"It's quite expensive."

"The cost is too high."

More IBM InfoSphere DataStage pricing and cost advice

"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

28%

Computer Software Company

10%

Manufacturing Company

Government

Financial Services Firm

26%

Computer Software Company

17%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

Would you upgrade to more premium versions of IBM InfoSphere DataStage?

My company currently uses the free version of the product, and we are definitely switching to a paid one. We needed a tool that can help us not only integrate our data but use it effectively. For ...

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Is IBM InfoSphere DataStage more difficult to use compared to other tools in the field?

I think the tool may cause some difficulties if you have not used other data integration solutions before. I have worked at companies that used different tools for data integration, and they work ...

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Do you rely on IBM Cloud Paks for your data? Have you utilized this product, or do you use IBM InfoSphere DataStage without it?

IBM Cloud Paks makes a big difference in your data integration. My company has been using it alongside IBM InfoSphere DataStage and while the main product is good on its own, this one truly expands...

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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...

See all answers

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...

See all answers

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...

See all answers

Comparisons

IBM Cloud Pak for Data vs IBM InfoSphere DataStage

Compared 14% of the time

SSIS vs IBM InfoSphere DataStage

Compared 11% of the time

Talend Open Studio vs IBM InfoSphere DataStage

Compared 10% of the time

Informatica PowerCenter vs IBM InfoSphere DataStage

Compared 7% of the time

IBM InfoSphere Information Server vs IBM InfoSphere DataStage

Compared 7% of the time

More IBM InfoSphere DataStage Competitors

Apache Flink vs Spring Cloud Data Flow

Compared 40% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 11% of the time

Google Cloud Dataflow vs Spring Cloud Data Flow

Compared 6% of the time

MuleSoft Anypoint Platform vs Spring Cloud Data Flow

Compared 6% of the time

Oracle Data Integrator (ODI) vs Spring Cloud Data Flow

Compared 2% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

IBM InfoSphere DataStage

April 2025

Download IBM InfoSphere DataStage product report

Buyer's Guide

Spring Cloud Data Flow

June 2025

Download Spring Cloud Data Flow product report

Overview

IBM InfoSphere DataStage is a high-quality data integration tool that aims to design, develop, and run jobs that move and transform data for organizations of different sizes. The product works by integrating data across multiple systems through a high-performance parallel framework. It supports extended metadata management, enterprise connectivity, and integration of all types of data.

The solution is the data integration component of IBM InfoSphere Information Server, providing a graphical framework for moving data from source systems to target systems. IBM InfoSphere DataStage can deliver data to data warehouses, data marts, operational data sources, and other enterprise applications. The tool works with various types of patterns - extract, transform and load (ETL), and extract, load, and transform (ELT). The scalability of the platform is achieved by using parallel processing and enterprise connectivity.

The solution has various versions, catering to different types of companies, which include the Server Edition, the Enterprise Edition, and the MVS Edition. Depending on which version a company has bought, different goals can be achieved. They include the following:

Designing data flows to extract information from multiple sources, transform the data, and deliver it to target databases or applications.
Delivery of relevant and accurate data through direct connections to enterprise applications.
Reduction of development time and improvement of consistency through prebuilt functions.
Utilization of InfoSphere Information Server tools for accelerating the project delivery cycle.

IBM InfoSphere DataStage can be deployed in various ways, including:

As a service: The tool can be accessed from a subscription model, where its capabilities are a part of IBM DataStage on IBM Cloud Park for Data as a Service. This option offers full management on IBM Cloud.
On premises or in any cloud: The two editions - IBM DataStage Enterprise and IBM DataStage Enterprise Plus - can run workloads on premises or in any cloud when added to IBM DataStage on IBM Cloud Pak for Data as a Service.
On premises: The basic jobs of the tool can be run on premises using IBM DataStage.

IBM InfoSphere DataStage Features

The tool has various features through which users can integrate and utilize their data effectively. The components of IBM InfoSphere DataStage include:

AI services: The tool offers services such as data science, event messaging, data warehousing, and data virtualization. It accelerates processes through artificial intelligence (AI) and offers a connection with IBM Cloud Paks - the cloud-native insight platform of the solution.
Parallel engine: Through this feature, ETL performance can be optimized to process data at scale. This is achieved through parallel engine and load balancing, which maximizes throughput.
Metadata support: This feature of the product uses the IBM Watson Knowledge Catalog to protect companies' sensitive data and monitor who can access it and at what levels.
Automated delivery pipelines: IBM InfoSphere DataStage reduces costs by automating continuous integration and delivery of pipelines.
Prebuilt connectors: The feature for prebuilt connectivity and stages allows users to move data between multiple cloud sources and data warehouses, including IBM native products.
IBM DataStage Flow Designer: This feature offers assistance through machine learning design. The product offers its clients a user-friendly interface which facilitates the work process.
IBM InfoSphere QualityStage: The tool provides a feature that automatically resolves data quality issues and increases the reliability of the delivered data.
Automated failure detection: Through this feature, companies can reduce infrastructure management efforts, relying on the automated detection that the tool offers.
Distributed data processing: Cloud runtimes can be executed remotely through this feature while maintaining its sovereignty and decreasing costs.

IBM InfoSphere DataStage Benefits

This solution offers many benefits for the companies that utilize it for data integration. Some of these benefits include:

Increased speed of workload execution due to better balancing and a parallel engine.
Reduction of data movement costs through integrations and seamless design of jobs.
Modernization of data integration by extending the capabilities of companies' data.
Delivery of reliable data through IBM Cloud Pak for Data.
Utilization of a drag-and-drop interface which assists in the delivery of data without the need for code.
Effective data manipulation allows data to be merged before being mapped and transformed.
Creating easier access of users to their data by providing visual maps of the process and the delivered data.

Reviews from Real Users

A data/solution architect at a computer software company says the product is robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data.

Tirthankar Roy Chowdhury, team leader at Tata Consultancy Services, feels the tool is user-friendly with a lot of functionalities, and doesn't require much coding because of its drag-and-drop features.

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.

VMware

Sample Customers

Dubai Statistics Center, Etisalat Egypt

Information Not Available

Buyer's Guide

IBM InfoSphere DataStage vs. Spring Cloud Data Flow

July 2025

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