SAP Data Hub [EOL] vs SAS Data Management comparison

SAP and SAS are both solutions in the Data Governance category. Additionally, 66% of SAP users are willing to recommend the solution, compared to 88% of SAS users who would recommend it.

SAP Data Hub [EOL]

Read 3 SAP Data Hub [EOL] reviews

66% willing to recommend

SAS Data Management

Read 18 SAS Data Management reviews

3,799 Views
1,178 Comparison Views

88% willing to recommend

SAP Data Hub [EOL]

SAS Data Management

Comparison Buyer's Guide

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Executive SummaryUpdated on Apr 15, 2026

SAS Data Management and SAP Data Hub [EOL] are competing in data management. SAP Data Hub [EOL] might have the upper hand due to its comprehensive integration capabilities despite SAS's strong data quality focus.

Features: SAS Data Management provides powerful data cleansing, quality enhancement, and reliability assurance tools. SAP Data Hub [EOL] integrates distributed data sources effectively, offering a unified view and is crucial for complex data environments without repeating the same data quality features of SAS.

Ease of Deployment and Customer Service: SAS Data Management facilitates a seamless deployment process with robust support for various business requirements, making it accessible. SAP Data Hub [EOL] involves a more intricate deployment but benefits from detailed integration support, distinguishing its approach with extensive integration focus.

Pricing and ROI: SAS Data Management often demands a higher upfront cost but delivers high ROI through enhanced data quality. SAP Data Hub [EOL] offers a potentially flexible pricing model concentrating on long-term gains, proving cost-effective for data integration-focused organizations, emphasizing integration and scalability.

To learn more, read our detailed Data Governance Report (Updated: April 2026).

Buyer's Guide

Data Governance

April 2026

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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

SAP Data Hub [EOL]

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

SAS Data Management

Average Rating

8.6

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Integration (28th), Data Quality (7th), Data Governance (23rd)

Featured Reviews

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.

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Fernanda Knopki

Data Scientist & Scrum Master at Volvo Group

Has supported centralized data access and improved governance through unified administration

The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS. The data integration tools with SAS Data Management were quite good because they allowed me to do all lineage, to manage and see all the variables, find the libraries where the data is, and understand the data in just one tool. Offering another development environment combining code and predefined objects, where I could just drag and drop to achieve what I needed, although some objects were not too good, but some were effective. The metadata management feature of SAS Data Management helps a lot; creating your data marts or data lake with good naming conventions, library conventions, and so on is very important because it allows easy queries to find the whole structure, though I think metadata governance also depends on first definitions, not only on the tool. SAS Data Management is very good for data governance; for me, it was the best tool I worked with in data management, although I don't have too much experience with others, and it truly helped a lot.

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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

"Having this solution enables us to approach our clients to upgrade their databases, and we upgrade them according to their business requirements."

"They lead in terms of business functions, and no other solution has business functions already implemented to perform business analysis, with a lot of prebuilt business functions for machine learning and orchestration that we can use directly to get an analysis out from the existing enterprise data."

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

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

"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."

"DataFlux in my opinion is an excellent high end solution for enterprise wide data management."

"The monitoring capabilities are very good."

"The tool is reliable, quick, and powerful."

"For the warehouse and BI environment, SAS is very quick, very intuitive, very, very powerful, and very valuable."

"The interface of the solution is great, you don't need to be an experienced analytics person to work with the product, and even new users can do all sorts of modeling on the data."

"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."

"I think the product is very stable, I think it's a marvelous product, it is very widely used by many people and I never hear people complain."

"The tool is reliable, quick, and powerful."

More SAS Data Management pros

Cons

"The company has everything offshore."

"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."

"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."

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

"Costly. Not great for non-ETL use cases."

"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."

"Complex, as usual with SAS"

"The pricing of the solution needs to be improved. They need to work to make it more affordable."

"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools."

"With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce; it's not a straightforward process."

"The stability could be a bit better. It's lacking in this area right now."

"The solution is quite expensive and hard to install/configure."

More SAS Data Management cons

Pricing and Cost Advice

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

"The tool is a bit expensive."

"The solution is expensive."

"The licensing model for vCenter is a perpetual license with yearly payments."

"While it is even free for personal use on the cloud, it can be expensive for desktop installations and enterprise use."

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Top Industries

By visitors reading reviews

Manufacturing Company

17%

Financial Services Firm

13%

Construction Company

Government

Financial Services Firm

20%

Healthcare Company

Government

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	8

Questions from the Community

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What is your experience regarding pricing and costs for SAS Data Management?

From my experience, SAS Data Management is an expensive tool.

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What needs improvement with SAS Data Management?

There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.

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What is your primary use case for SAS Data Management?

The main idea for using SAS Data Management was to bring all data inside SAS. I brought the finance area and the sales area in the company that I have worked, along with some market planning data, ...

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Comparisons

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Compared 12% of the time

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Compared 11% of the time

Oracle Data Integrator (ODI) vs SAP Data Hub [EOL]

Compared 9% of the time

Microsoft Purview Data Governance vs SAP Data Hub [EOL]

Compared 6% of the time

Palantir Foundry vs SAP Data Hub [EOL]

Compared 6% of the time

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Informatica PowerCenter vs SAS Data Management

Compared 10% of the time

WhereScape RED vs SAS Data Management

Compared 9% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs SAS Data Management

Compared 8% of the time

Collibra Platform vs SAS Data Management

Compared 5% of the time

Qlik Talend Cloud vs SAS Data Management

Compared 5% of the time

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Product Reports

Buyer's Guide

Data Governance

April 2026

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Buyer's Guide

SAS Data Management

April 2026

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Also Known As

No data available

SAS Data Management Platform, Data Management Platform, DataFlux

Overview

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

SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.

SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.

What are the key features of SAS Data Management?

User-friendly interface: Intuitive navigation facilitates ease of use.
Easy data flow creation: Streamlines processes for seamless data management.
Scheduling and ETL control: Automates tasks for increased efficiency.
Data integration: Connects datasets from multiple origins.
Metadata management: Ensures consistency and quality of data.
Data governance: Provides tools for managing data compliance.
Robust reporting: Delivers comprehensive insights through detailed reports.

What benefits and ROI should be considered?

Data standardization: Enhances data predictability and usability.
Data quality management: Improves accuracy and integrity.
Flexible language: Adapts to specific user requirements.
Import/export capabilities: Facilitates seamless data transitions.
Support for diverse users: Offers tools suitable for varied skill levels.
Automation features: Saves time by reducing manual processes.

SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.

SAS

Sample Customers

Kaeser Kompressoren, HARTMANN

Data Management, 1-800-FLOWERS.COM, Absa, Aegon, Allianz Global Corporate & SpecialtyAusgrid, Bank of Queensland, Bell, BMC Software, Canada Post, Ceska pojistovna, Chantecler, Chubb Group of Insurance Companies, Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Enerjisa, ERGO Insurance Group, Florida Department of Corrections, Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, North Carolina Office of Information Technology Services, Orlando Magic, OTP Group, PITT OHIO, Plano Independent School District, RWE Poland, Spanish Air Force, Stockholm County Council, Telus, The Travel Corporation, Transitions Optical, Triad Analytic Solutions, UNIQA, US Census Bureau, US Department of Housing and Urban Development, USDA National Agricultural Statistics Service, West Midlands Police, XS Inc., Zenith Insurance

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