IBM InfoSphere DataStage vs SAP Data Hub comparison

The compared IBM and SAP solutions aren't in the same category. IBM is ranked #6 in DI , with an average rating of 8.1, and holds a 5.0% mindshare in the category. SAP is ranked #29 in DG , with an average rating of 7.0, and holds a 1.1% mindshare. Additionally, 83% of IBM users are willing to recommend the solution, compared to 66% of SAP users who would recommend it.

IBM InfoSphere DataStage

Read 42 IBM InfoSphere DataStage reviews

6,426 Views
4,298 Comparison Views

83% willing to recommend

SAP Data Hub

Read 3 SAP Data Hub reviews

552 Views
363 Comparison Views

66% willing to recommend

IBM InfoSphere DataStage

SAP Data Hub

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between IBM InfoSphere DataStage and SAP Data Hub based on real PeerSpot user reviews.

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: June 2025).

Buyer's Guide

Data Integration

June 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

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (6th)

SAP Data Hub

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Governance (29th), Metadata Management (10th)

Mindshare comparison

IBM InfoSphere DataStage and SAP Data Hub aren’t in the same category and serve different purposes. IBM InfoSphere DataStage is designed for Data Integration and holds a mindshare of 5.0%, down 5.6% compared to last year.
SAP Data Hub, on the other hand, focuses on Data Governance, holds 1.1% mindshare, down 1.2% since last year.

Data Integration

Data Governance

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

Vijaya Macherla

GTM Lead at Capgemini

The solution is seamless, but the database sometimes leads to confusion

We used to have multiple different kinds of databases, which internally, had different compliance levels. Retention management is very different now. If the policy is live and the claim has been completed, I couldn't archive the claim. I needed to keep a reference integrity of that claim and understand which policy paid out the claim. With this solution, the policy came in six months ago and qualified for archiving. The claim had been paid and in every environment, the claim had been closed, including the reporting system, the claims system, etc. With the payment set gateway, I can just go and archive. But, we had a hard time during this process. I rate the overall solution a seven out of ten.

Read full review

Quotes from Members

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

Pros

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

"The solution is stable."

"It works with multiple servers and offers high availability."

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

"DataStage works better with Linux operating systems when the application services are hosted on Linux system equipment, but it's powerful on Windows too."

"The Hierarchical Data Stage is good."

"The solution has improved the time it takes to perform tasks related to batch applications."

"We can view what we want to do. We can transform data and put them on tables."

More IBM InfoSphere DataStage pros

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."

"The most valuable feature is the S/4HANA 1909 On-Premise"

Cons

"Currently lacking virtualization ability."

"We would be happy to see in next versions the ability to return several parameters from jobs. Now, jobs can return just one parameter. If they could return several parameters, that would be great."

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

"I'd like to be able to do more with the data and metadata, including copy and pasting, et cetera."

"I wonder if it supports other areas, such as cloud environments with open source support, or EdgeShift."

"The troubleshooting guide is very bad."

"The solution needs improvement in connectivity with big data technologies such as Spark."

"There could be more customization options for the product."

More IBM InfoSphere DataStage cons

"The company has everything offshore."

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."

Pricing and Cost Advice

"It's very expensive."

"The pricing is competitive but on the higher side of the pricing scale."

"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 pricing depends on the setup. However, we paid $100,000 as a one-time cost for an on-premises setup."

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

"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."

"Pricing varies based on use, and it is not as costly as some competing enterprise solutions."

More IBM InfoSphere DataStage pricing and cost advice

"The Cloud is very expensive, but SAP HANA previous service is okay."

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Top Industries

By visitors reading reviews

Financial Services Firm

28%

Computer Software Company

11%

Manufacturing Company

Government

Financial Services Firm

16%

Computer Software Company

14%

Manufacturing Company

12%

Government

12%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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 ...

See all answers

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 ...

See all answers

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...

See all answers

What do you like most about SAP Data Hub?

SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database.

See all answers

What needs improvement with SAP Data Hub?

We moved from Oracle. If you're aware of your monitoring system, the RPU market, and the managed system, you should move to HANA, which is an innovative database built by SAP itself. However, this ...

See all answers

What is your primary use case for SAP Data Hub?

I technically handle the database, like cycle management projects. When transaction data comes in, we see it based on the retention periods. We have to move the data to some secure storage rather t...

See all answers

Comparisons

IBM Cloud Pak for Data vs IBM InfoSphere DataStage

Compared 13% of the time

SSIS vs IBM InfoSphere DataStage

Compared 11% of the time

Talend Open Studio vs IBM InfoSphere DataStage

Compared 11% of the time

Azure Data Factory vs IBM InfoSphere DataStage

Compared 8% of the time

Informatica PowerCenter vs IBM InfoSphere DataStage

Compared 8% of the time

More IBM InfoSphere DataStage Competitors

Microsoft Purview Data Governance vs SAP Data Hub

Compared 31% of the time

Palantir Foundry vs SAP Data Hub

Compared 22% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs SAP Data Hub

Compared 17% of the time

Collibra Governance vs SAP Data Hub

Compared 8% of the time

Alation Data Catalog vs SAP Data Hub

Compared 6% of the time

More SAP Data Hub Competitors

Product Reports

Buyer's Guide

IBM InfoSphere DataStage

April 2025

Download IBM InfoSphere DataStage product report

Buyer's Guide

Data Governance

June 2025

Download SAP Data Hub 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

The SAP® Data Hub solution enables sophisticated data operations management. It gives you the capability and flexibility to connect enterprise data and Big Data and gain a deep understanding of data and information processes across sources and systems throughout the distributed landscape. The unified solution provides visibility and control into data opportunities, integrating cloud and on-premise information and driving data agility and business value. Distributed processing power enables greater speed and efficiency.

SAP

Sample Customers

Dubai Statistics Center, Etisalat Egypt

Kaeser Kompressoren, HARTMANN

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration. Updated: June 2025.

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