IBM Cloud Pak for Data vs SAS Access comparison

IBM and SAS are both solutions in the Data Integration category. IBM is ranked #24 with an average rating of 8.0, while SAS is ranked #56. IBM holds a 1.9% mindshare in DI, compared to SAS’s 0.3% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 100% of SAS users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

2,494 Views
1,410 Comparison Views

86% willing to recommend

SAS Access

Read 3 SAS Access reviews

273 Views
174 Comparison Views

100% willing to recommend

IBM Cloud Pak for Data

SAS Access

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

SAS Access and IBM Cloud Pak for Data are competitors in the data management and analytics space. IBM Cloud Pak for Data appears superior due to its comprehensive suite of analytic tools, offering extensive data processing capabilities.

Features: SAS Access integrates with varied data sources, offers robust connectivity, and is ideal for specific integrations. IBM Cloud Pak for Data provides an end-to-end solution, supports multi-cloud environments, and offers AI-driven analytics, making it versatile for complex data environments.

Ease of Deployment and Customer Service: SAS Access is noted for straightforward deployment and reliable customer support, beneficial for organizations with limited IT resources. IBM Cloud Pak for Data uses containerized deployment, offering flexibility for cloud-native architectures but requires more infrastructure expertise.

Pricing and ROI: SAS Access has a lower initial setup cost, supporting quicker ROI for smaller projects. IBM Cloud Pak for Data demands higher investment but offers potentially higher ROI through extended capabilities, suitable for large-scale deployments.

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

Buyer's Guide

IBM Cloud Pak for Data vs. SAS Access

June 2025

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Helped 856,873 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 Access

Ranking in Data Integration

56th

Average Rating

9.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.9%, up from 1.7% compared to the previous year. The mindshare of SAS Access is 0.3%, up from 0.2% 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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Robert Heck

Co Owner at Hecht und Heck GmbH

The solution is stable, scalable, and flexible

I rate the solution eight out of ten. The number of people required to maintain the solution is dependent on the other applications running. The solution in itself does not require a lot of maintenance. The solution is flexible and I recommend it when you have more complex applications with special requirements.

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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

"Its data preparation capabilities are highly valuable."

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

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

"IBM Watson Catalog and data pipelines are the most valuable features of the solution."

"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."

"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."

"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."

"Cloud Pak is a very, very, very good system."

More IBM Cloud Pak for Data pros

"The most valuable part of SAS/ACCESS is what it is made for: connecting to remote systems that are not part of your physical SAS environment."

"The most valuable feature is you have native access to the external databases."

"The most valuable aspect of the solution is the ease of access to the data in those databases."

Cons

"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."

"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."

"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."

"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 thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

"The product must improve its performance."

"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."

More IBM Cloud Pak for Data cons

"The pricing model needs to be reconsidered and adjusted."

"The solution can provide access to the newer databases that come out sooner."

"I can't really recall any missing feature or general improvement that is needed. We don't really add too many new kinds of databases and therefore our needs are already met."

Pricing and Cost Advice

"It's quite expensive."

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

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

"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."

"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."

"The pricing model is complex and is based on modular packages as well as the size of the applicable environment."

"The solution's pricing and licensing are expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

30%

Manufacturing Company

10%

Computer Software Company

10%

Government

Financial Services Firm

27%

Computer Software Company

10%

Insurance Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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

DataStage allows me to connect to different data sources.

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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.

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What needs improvement with IBM Cloud Pak for Data?

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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 15% of the time

Denodo vs IBM Cloud Pak for Data

Compared 13% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 10% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 9% of the time

More IBM Cloud Pak for Data Competitors

Teradata vs SAS Access

Compared 100% of the time

More SAS Access Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

June 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

Data Integration

June 2025

Download SAS Access product report

Also Known As

Cloud Pak for Data

SAS/Access

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

SAS/ACCESS is an out-of-the-box solution for integrating SAS and third-party databases. You can read, write and update data regardless of the database or platform. Because the data appears native to SAS, there is no need to learn Structured Query Language (SQL) or any other database-specific query languages.

SAS

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Los Angeles County, West Midlands Police, Credit Guarantee Corporation, Canada Post, Allianz Global Corporate & Specialty

Buyer's Guide

IBM Cloud Pak for Data vs. SAS Access

June 2025

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

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