SAS Data Management vs StreamSets comparison

SAS and IBM are both solutions in the Data Integration category. SAS is ranked #26 with an average rating of 9.3, while IBM is ranked #22 with an average rating of 9.5. SAS holds a 1.2% mindshare in DI, compared to IBM’s 1.2% mindshare. Additionally, 88% of SAS users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

SAS Data Management

Read 19 SAS Data Management reviews

4,330 Views
2,425 Comparison Views

88% willing to recommend

StreamSets

Read 21 StreamSets reviews

3,842 Views
2,920 Comparison Views

100% willing to recommend

SAS Data Management

StreamSets

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

SAS Data Management and StreamSets both fall within the data management category, specializing in ETL and data integration solutions. While SAS Data Management offers a robust suite of tools suitable for complex enterprise needs, StreamSets provides a simpler, more accessible platform for non-technical users.

Features: SAS Data Management provides powerful data quality, integration, and governance features, along with strong ETL and data analysis capabilities designed for complex data environments across diverse platforms. StreamSets offers a user-friendly no-code platform, focusing on real-time data processing, connectivity options, and effectively managing data drift and transformations.

Room for Improvement: SAS Data Management could enhance its documentation, simplify database connectivity and integration with non-SAS tools, and address its expensive licensing model. StreamSets needs improvements in logging mechanisms, UI enhancements, real-time processing capabilities, and addressing high licensing costs and technical support issues.

Ease of Deployment and Customer Service: SAS Data Management operates primarily on-premises, offering moderate support, with some reports of complex technical problem-solving difficulties. StreamSets supports diverse deployment options in public, hybrid, and on-premises clouds, praised for simple deployments but noted for expensive support and limited knowledge base resources.

Pricing and ROI: SAS Data Management is known for its high cost, justified by comprehensive features leading to significant ROI, especially in industries with stringent data needs. StreamSets provides an open-source version, but its paid versions are costly, offering a flexible pricing model and delivering high ROI through efficient data operations despite occasional costly updates.

To learn more, read our detailed SAS Data Management vs. StreamSets Report (Updated: June 2026).

Buyer's Guide

SAS Data Management vs. StreamSets

June 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:

ROI

Sentiment score

6.1

SAS Data Management enhances ROI by improving data accuracy and reliability while reducing costs, especially for larger organizations.

Sentiment score

8.1

StreamSets speeds up data processing, boosts efficiency and revenue, simplifies tasks, enhances security, and reduces costs significantly.

Reliable data plus less human intervention and less error result in a strong return on investment.

Namanjbaraiya Baru

Biostatistician at Lambda Therapeutic Research Ltd.

For more quotes and insights, download the SAS Data Management report

No quotes available

For more quotes and insights, download the StreamSets report

Customer Service

Sentiment score

7.3

SAS Data Management customer service is praised for responsiveness and expertise, but experiences vary by region and complexity.

Sentiment score

6.7

StreamSets support is responsive and knowledgeable, offering effective solutions, though response times and technical handling could improve.

The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.

Fernanda Knopki

Data Scientist & Scrum Master at Volvo Group

For more quotes and insights, download the SAS Data Management report

IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.

SrinivasanSankar

Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees

For more quotes and insights, download the StreamSets report

Scalability Issues

Sentiment score

7.0

SAS Data Management is scalable and adaptable, efficiently handling extensive data and users across various roles and locations.

Sentiment score

7.6

StreamSets is scalable and flexible, favored for cloud use but could improve auto-scaling for large data migrations.

No quotes available

For more quotes and insights, download the SAS Data Management report

No quotes available

For more quotes and insights, download the StreamSets report

Stability Issues

Sentiment score

7.3

SAS Data Management is stable and efficient, excelling on Linux, though minor issues exist with the Windows client.

Sentiment score

7.8

StreamSets is praised for stability and reliability, despite minor memory issues, with high user ratings and market competitiveness.

No quotes available

For more quotes and insights, download the SAS Data Management report

No quotes available

For more quotes and insights, download the StreamSets report

Room For Improvement

Users seek cost-effective improvements in installation, integration, analytics, cloud scalability, user interface, documentation, and data sharing capabilities.

StreamSets struggles with integration, real-time processing, clarity in UI, memory issues, security, documentation, and cloud storage performance.

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

SantoshTiwari

Associate Director at Woodpecker Analytics & Services

SAS Data Management can be improved in terms of the learning curve.

Namanjbaraiya Baru

Biostatistician at Lambda Therapeutic Research Ltd.

For more quotes and insights, download the SAS Data Management report

It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.

SrinivasanSankar

Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees

For more quotes and insights, download the StreamSets report

Setup Cost

SAS Data Management's robust features lead to high costs, perceived as valuable, yet budget constraints may limit adoption.

StreamSets provides flexible pricing models, with varied user satisfaction, favoring larger enterprises over smaller companies due to cost.

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

SantoshTiwari

Associate Director at Woodpecker Analytics & Services

For more quotes and insights, download the SAS Data Management report

No quotes available

For more quotes and insights, download the StreamSets report

Valuable Features

SAS Data Management provides reliable interfaces, robust governance, analytics, and security, making it ideal for diverse industries and users.

StreamSets offers intuitive interface, extensive connectors, and features accessible to non-technical users for seamless data integration and manipulation.

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.

Fernanda Knopki

Data Scientist & Scrum Master at Volvo Group

It is very reliable, very time-saving, and the chances of error are minimal.

Namanjbaraiya Baru

Biostatistician at Lambda Therapeutic Research Ltd.

SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.

SantoshTiwari

Associate Director at Woodpecker Analytics & Services

For more quotes and insights, download the SAS Data Management report

It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.

SrinivasanSankar

Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees

For more quotes and insights, download the StreamSets report

Categories and Ranking

SAS Data Management

Ranking in Data Integration

26th

Average Rating

8.6

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Quality (6th), Data Governance (24th)

StreamSets

Ranking in Data Integration

22nd

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2026, in the Data Integration category, the mindshare of SAS Data Management is 1.2%, up from 0.9% compared to the previous year. The mindshare of StreamSets is 1.2%, down from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
StreamSets	1.2%
SAS Data Management	1.2%
Other	97.6%

Data Integration

Featured Reviews

Namanjbaraiya Baru

Biostatistician at Lambda Therapeutic Research Ltd.

Data management has ensured compliant clinical trial datasets and supports reliable analysis

SAS Data Management's best feature is first, data reliability because SAS Data Management is a very trusted platform. The other valuable feature is data cleaning and the compliance that SAS Data Management provides. I can connect SAS Data Management with other SAS applications, as I am using SAS Viya, SAS 9.4, and SAS Enterprise Guide. The data query functionality of SAS Data Management is also very useful. Since I am using SAS Data Management, and SAS Data Management is well trusted by all regulatory authorities, the audit trails and security checks are very good. It is very reliable, very time-saving, and the chances of error are minimal.

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SrinivasanSankar

Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees

Enables effective batch loading with visual interface and enterprise support

One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infrastructure. I had to switch to a new EC2 box, even though the processor was not fully utilized. It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades. Additionally, it would be a great enhancement if StreamSets could produce a lineage graph to visualize how the data has passed through the system.

Read full review

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Government

Comms Service Provider

Construction Company

Financial Services Firm

12%

Manufacturing Company

Insurance Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	2
Large Enterprise	8

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	2
Large Enterprise	11

Questions from the Community

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?

SAS Data Management can be improved in terms of the learning curve.

See all answers

What is your primary use case for SAS Data Management?

My main use case for using SAS Data Management is data cleaning for my clinical trial data because my data is very large, and I need clean, reliable, and regulatory compliance data. My data comes f...

See all answers

What needs improvement with StreamSets?

See all answers

What is your primary use case for StreamSets?

We are using StreamSets for batch loading.

See all answers

What advice do you have for others considering StreamSets?

If asked, I definitely recommend StreamSets to other users. My overall rating for the solution is nine.

See all answers

Comparisons

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Compared 9% of the time

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Compared 8% of the time

WhereScape RED 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 4% of the time

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Pentaho Data Integration and Analytics vs StreamSets

Compared 8% of the time

Informatica PowerCenter vs StreamSets

Compared 6% of the time

SSIS vs StreamSets

Compared 5% of the time

Confluent vs StreamSets

Compared 5% of the time

Spring Cloud Data Flow vs StreamSets

Compared 4% of the time

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Product Reports

Buyer's Guide

SAS Data Management

May 2026

Download SAS Data Management product report

Buyer's Guide

StreamSets

May 2026

Download StreamSets product report

Also Known As

SAS Data Management Platform, Data Management Platform, DataFlux

No data available

Overview

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

StreamSets streamlines data pipeline creation, connecting data from multiple sources to destinations like cloud platforms with minimal coding. Its centralized platform and intuitive design enhance ETL and data migration processes.

StreamSets integrates seamlessly with analytics platforms, offering tools such as Data Collector and Control Hub to facilitate data ingestion, transformation, and machine learning integrations. Its user-friendly interface and ready connectors aid in configuring complex data pipelines. With built-in data drift resilience and scheduling options, users experience efficient, scalable data management, despite challenges like latency in cloud storage and interface enhancement needs. Users often employ StreamSets for batch loading, real-time data processing, and smart data pipeline management, offering comprehensive data integration solutions.

What are the key features of StreamSets?

Data Collector: Enables streamlined data collection and processing.
Control Hub: Centralizes management of data pipelines.
Minimal Coding: Simplifies pipeline configuration with limited code requirement.
Data Drift Resilience: Adapts to changes in data patterns effectively.

What benefits should users look for?

Time-Saving: Efficient processes reduce manual effort.
Scalability: Easily manages large datasets.
Integration: Connects with leading analytics and cloud platforms.
Real-Time Processing: Supports continuous data delivery for timely insights.

In industries like finance and technology, StreamSets supports data migration, machine learning integrations, and analytics by simplifying data transformation and enhancing decision-making capabilities through its robust pipeline management.

IBM

Sample Customers

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

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

SAS Data Management vs. StreamSets

June 2026

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