IBM Cloud Pak for Data vs SAS Data Management comparison

IBM and SAS are both solutions in the Data Integration category. IBM is ranked #16 with an average rating of 8.2, while SAS is ranked #35 with an average rating of 7.5. IBM holds a 1.8% mindshare in DI, compared to SAS’s 0.7% 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

2,778 Views
1,932 Comparison Views

86% willing to recommend

SAS Data Management

Read 17 SAS Data Management reviews

940 Views
758 Comparison Views

87% willing to recommend

IBM Cloud Pak for Data

SAS Data Management

Comparison Buyer's Guide

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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: April 2025).

Buyer's Guide

IBM Cloud Pak for Data vs. SAS Data Management

April 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

16th

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

35th

Average Rating

8.4

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Quality (11th), Data Governance (26th)

Mindshare comparison

As of April 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 SAS Data Management is 0.7%, 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.

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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.

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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

"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."

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

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

"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."

"Scalability-wise, I rate the solution a nine or ten 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."

"DataStage allows me to connect to different data sources."

More IBM Cloud Pak for Data pros

"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."

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

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

"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."

"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 technical support is excellent."

"I find the solution to be very stable."

More SAS Data Management pros

Cons

"The solution's user experience is an area that has room for improvement."

"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."

"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."

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

"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."

"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

"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."

"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."

"I would like the tool to include the ability to automate the modifications of the integrations."

"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."

"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."

"The solution could use better documentation."

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

More SAS Data Management cons

Pricing and Cost Advice

"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."

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

"It's quite expensive."

"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."

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

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

"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."

"The solution is expensive."

"The tool is a bit expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

11%

Manufacturing Company

10%

Insurance Company

Financial Services Firm

29%

Computer Software Company

13%

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 do you like most about SAS Data Management?

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

See all answers

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

The licensing model for vCenter is a perpetual license with yearly payments. This model ensures continuous updates and support while managing initial setup costs.

See all answers

What needs improvement with SAS Data Management?

Integration and cloud migration are areas where we see potential for improvement. A more seamless integration process and transitioning to a cloud-based environment would enhance user-friendliness ...

See all answers

Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 41% of the time

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

Compared 16% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 11% of the time

Denodo vs IBM Cloud Pak for Data

Compared 11% 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 20% of the time

Palantir Foundry vs SAS Data Management

Compared 16% of the time

Informatica PowerCenter vs SAS Data Management

Compared 13% of the time

Collibra Governance vs SAS Data Management

Compared 11% of the time

Talend Open Studio vs SAS Data Management

Compared 9% of the time

More SAS Data Management Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

April 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

SAS Data Management

March 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

April 2025

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

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