IBM Cloud Pak for Data vs SAS Data Management comparison

IBM and SAS are both solutions in the Data Integration category. IBM is ranked #24 with an average rating of 7.7, while SAS is ranked #30 with an average rating of 8.0. IBM holds a 2.0% mindshare in DI, compared to SAS’s 1.0% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 87% of SAS users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

2,349 Views
2,208 Comparison Views

86% willing to recommend

SAS Data Management

Read 17 SAS Data Management reviews

1,524 Views
869 Comparison Views

87% willing to recommend

IBM Cloud Pak for Data

SAS Data Management

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 19, 2024

SAS Data Management and IBM Cloud Pak for Data compete in the data management solutions category. IBM Cloud Pak for Data holds an advantage due to user endorsements for its integration and functionality capabilities.

Features: SAS Data Management excels in ETL processes, data quality, and data governance. It provides a unified view of enterprise data and supports multiple data sources through ODBC drivers. SAS's interface is user-friendly, even for non-technical users. IBM Cloud Pak for Data offers strong containerization and data virtualization. It incorporates Watson Knowledge Catalog, enhancing data governance and AI integration. It also features components for seamless cloud transitions.

Room for Improvement: SAS Data Management faces high licensing costs and requires stronger capabilities beyond ETL and improved database connectivity. IBM Cloud Pak for Data needs enhanced machine learning lifecycle management and a more streamlined installation. Users indicate complexity in cloud transitions and infrastructure needs.

Ease of Deployment and Customer Service: SAS Data Management is primarily on-premises, with mixed feedback on customer support due to accessibility and expertise issues. IBM Cloud Pak for Data fits cloud and hybrid deployments but can be complex to implement at scale. It offers dependable customer service to address deployment challenges.

Pricing and ROI: Both solutions are costly, with SAS Data Management yielding high satisfaction in sectors like pharmaceuticals due to compliance needs. IBM Cloud Pak for Data's expenses align with its extensive capabilities, although smaller enterprises may find affordability challenging. Both promise ROI in data reliability and efficiency gains.

To learn more, read our detailed IBM Cloud Pak for Data vs. SAS Data Management Report (Updated: July 2025).

Buyer's Guide

IBM Cloud Pak for Data vs. SAS Data Management

July 2025

Download the complete report

Helped 865,295 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

IBM Cloud Pak for Data

Ranking in Data Integration

24th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

SAS Data Management

Ranking in Data Integration

30th

Average Rating

8.4

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Quality (11th), Data Governance (25th)

Mindshare comparison

As of August 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 2.0%, up from 1.7% compared to the previous year. The mindshare of SAS Data Management is 1.0%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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.

Read full review

Vivek Trivedi

Head finance transformation at Ahli United Bank Ksc

Has robust data governance capabilities and efficient financial alerting features

The platform's robust data governance capabilities ensure strong compliance with regulatory standards. Our dedicated data governance team is responsible for setting policies and monitoring data access and usage. Additionally, we have a Data Protection Officer (DPO) and an independent InfoSec team that work together to enforce these policies. This multi-layered approach ensures that data governance is effectively managed and compliant with all necessary regulations. It is integrated with SQL and Power BI servers for executive management dashboard reporting. This integration supports comprehensive data analysis and reporting needs, which was a key factor in our decision. The value of using vCenter lies in its comprehensive data infrastructure management. It significantly enhances our reporting, day-to-day decision-making, and analytics capabilities. Integrating SaaS with vCenter adds value by streamlining key functions and improving overall organizational efficiency. The solution can be considered expensive, particularly due to infrastructure, maintenance, and ownership costs. The long-term savings and efficiencies gained from using vCenter can justify the investment for large organizations. However, the high costs might not be justifiable for smaller organizations with less data and fewer resources. Conducting a thorough cost-benefit analysis based on the organization's specific needs and scale is recommended. I rate it an eight.

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 features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."

"Its data preparation capabilities are highly valuable."

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

"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."

"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."

"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."

"The most valuable features are data virtualization and reporting."

"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."

More IBM Cloud Pak for Data pros

"I am impressed with the tool's ability to customize."

"The platform's robust data governance capabilities ensure strong compliance with regulatory standards."

"I find the solution to be very stable."

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

"This is an established product with powerful data analysis and varied options for user entry points."

"If you compare it to SQL, the memory and development times are very quick."

"The product offers very good flexibility."

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

More SAS Data Management pros

Cons

"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 solution's catalog searching or map search needs to be improved."

"Cloud Pak would be improved with integration with cloud service providers like Cloudera."

"The technical support could be a little better."

"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."

"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."

"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."

More IBM Cloud Pak for Data cons

"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."

"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."

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

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

"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. We can't open those data in other applications. So we need to have that application in place."

"Integration and cloud migration are areas where we see potential for improvement."

"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."

More SAS Data Management cons

Pricing and Cost Advice

"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."

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

"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."

"It's quite expensive."

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

"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 is expensive."

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

"The solution is expensive."

"The tool is a bit expensive."

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

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

865,295 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

30%

Manufacturing Company

11%

Computer Software Company

Government

Financial Services Firm

28%

Computer Software Company

Insurance Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM Cloud Pak for Data?

DataStage allows me to connect to different data sources.

See all answers

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.

See all answers

What needs improvement with IBM Cloud Pak for Data?

See all answers

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

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

See all answers

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.

See all answers

What is your primary use case for SAS Data Management?

Some clients and I are using SAS Data Management for data cleansing, data warehousing, and IoT-related activities such as streaming data.

See all answers

Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 40% of the time

Denodo vs IBM Cloud Pak for Data

Compared 12% of the time

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

Compared 10% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 9% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 8% of the time

More IBM Cloud Pak for Data Competitors

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

Compared 19% of the time

Palantir Foundry vs SAS Data Management

Compared 13% of the time

Collibra Governance vs SAS Data Management

Compared 12% of the time

Protegrity’s Data Protection Platform vs SAS Data Management

Compared 9% of the time

Informatica PowerCenter vs SAS Data Management

Compared 8% of the time

More SAS Data Management Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

August 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

SAS Data Management

July 2025

Download SAS Data Management product report

Also Known As

Cloud Pak for Data

SAS Data Management Platform, Data Management Platform, DataFlux

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

Every decision, every business move, every successful customer interaction - they all come down to high-quality, well-integrated data. If you don't have it, you don't win. SAS Data Management is an industry-leading solution built on a data quality platform that helps you improve, integrate and govern your data.

SAS

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

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

Buyer's Guide

IBM Cloud Pak for Data vs. SAS Data Management

July 2025

Free Report: IBM Cloud Pak for Data vs. SAS Data Management

Find out what your peers are saying about IBM Cloud Pak for Data vs. SAS Data Management and other solutions. Updated: July 2025.

DOWNLOAD NOW

865,295 professionals have used our research since 2012.

See our IBM Cloud Pak for Data vs. SAS Data Management report.

See our list of best Data Integration vendors.

We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.