SAS Data Management vs Syniti Data Quality comparison

SAS and Syniti are both solutions in the Data Quality category. SAS is ranked #8 with an average rating of 10.0, while Syniti is ranked #19. SAS holds a 3.2% mindshare in DQ, compared to Syniti’s 2.7% mindshare. Additionally, 88% of SAS users are willing to recommend the solution, compared to 100% of Syniti users who would recommend it.

SAS Data Management

Read 19 SAS Data Management reviews

5,073 Views
1,218 Comparison Views

88% willing to recommend

Syniti Data Quality

Read 4 Syniti Data Quality reviews

1,432 Views
1,418 Comparison Views

100% willing to recommend

SAS Data Management

Syniti Data Quality

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 6, 2025

SAS Data Management and Syniti Data Quality compete in data management. Syniti has the upper hand due to its superior features and personalized deployment assistance, despite higher costs.

Features: SAS Data Management offers robust data integration, governance, and analytics. Syniti Data Quality provides precision in data cleansing, efficient profiling, and real-time monitoring. The advantage lies in Syniti's advanced data quality features, preferred for comprehensive accuracy management.

Ease of Deployment and Customer Service: SAS Data Management ensures a streamlined deployment process with dedicated support. Syniti Data Quality provides tailored onboarding assistance and responsive support, appealing to organizations requiring detailed deployment help.

Pricing and ROI: SAS Data Management is noted for competitive pricing with a balance of costs and long-term benefits. Syniti Data Quality, while having higher initial costs, offers substantial ROI through enhanced data quality outcomes, suggesting potential long-term savings.

To learn more, read our detailed SAS Data Management vs. Syniti Data Quality Report (Updated: August 2026).

Buyer's Guide

SAS Data Management vs. Syniti Data Quality

August 2026

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Helped 909,725 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

SAS Data Management

Ranking in Data Quality

8th

Average Rating

8.6

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Integration (27th), Data Governance (23rd)

Syniti Data Quality

Ranking in Data Quality

19th

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Data Quality category, the mindshare of SAS Data Management is 3.2%, up from 3.2% compared to the previous year. The mindshare of Syniti Data Quality is 2.7%, down from 9.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Mindshare Distribution
Product	Mindshare (%)
SAS Data Management	3.2%
Syniti Data Quality	2.7%
Other	94.1%

Data Quality

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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Raj AB

Delivery Head at ApikinFotech

Offers predefined rules and easy to migrate data with minimum customisation of rules

The customization of the data needs improvement. We need to build basic SQL queries rather than being able to do it within the tool. We need to be able to analyze the SQL queries and then rerun them based on customer usage. We should be able to tune the existing process by using simple SQL queries based on the customer's requirements. In future releases, I would like to see more features around Preload and postload reports. From the end-user point of view, it is not very feasible to read. I need to know how the data has been migrated. I need to know whether the complete data has been migrated, only the required data has been migrated, and how it was migrated. So the postload reports will give validation between the source data and the target source. It would give exact picture of the data migration.

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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

"I find the solution to be very stable."

"The technical support is excellent."

"The ROI can be very high in terms of improving the reliability and accuracy of data used in forecasting and marketing models (ex: customer data, sales data)."

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

"Reliable data plus less human intervention and less error have made a significant difference."

"National Quality Knoledge Base Matching features QPI (Quality Performance Indicator) analysis approach"

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

"There is a huge ROI."

More SAS Data Management pros

"Syniti has built-in 80% of the solution, and we only need to customize 20 to 25% of the features. It is easy to run and pre-load reports."

"With Syniti Data Quality, you can integrate SAP and directly fix errors from Syniti Data Quality instead of logging into SAP and then fixing them."

"The customer service and support is good."

"The major benefits of Syniti Data Quality stem from the productivity and flexibility it offers to users."

Cons

"Complex, as usual with SAS"

"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."

"For the amount of features that we use, the licensing is expensive."

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

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

"The solution is very expensive."

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

More SAS Data Management cons

"In Syniti Data Quality, data extraction is an area with certain shortcomings where improvements are required."

"The customization of the data needs improvement. We need to build basic SQL queries rather than being able to do it within the tool. We need to be able to analyze the SQL queries and then rerun them based on customer usage."

"It would be good if Syniti Data Quality could integrate more AI in the future."

"The loading mechanisms and administration processes, particularly in setting up connections and deploying the system, need improvement."

Pricing and Cost Advice

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

"The tool is a bit expensive."

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

"The solution is expensive."

"I would rate the pricing a six out of ten, where one is cheap, and ten is expensive."

"The solution is expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Construction Company

Outsourcing Company

Comms Service Provider

Manufacturing Company

12%

Retailer

University

Consumer Goods 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

No data available

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...

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Compared 5% of the time

Qlik Talend Cloud vs SAS Data Management

Compared 4% of the time

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Compared 19% of the time

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Compared 14% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Syniti Data Quality

Compared 12% of the time

Qlik Talend Cloud vs Syniti Data Quality

Compared 8% of the time

Melissa Data Quality vs Syniti Data Quality

Compared 6% of the time

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Product Reports

Buyer's Guide

SAS Data Management

July 2026

Download SAS Data Management product report

Buyer's Guide

Data Quality

August 2026

Download Syniti Data Quality product report

Also Known As

SAS Data Management Platform, Data Management Platform, DataFlux

Syniti DQ

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

Syniti Data Quality enhances data management with comprehensive features tailored for accurate and efficient processing. It addresses critical data quality challenges, ensuring reliable decision-making through improved data integrity.

Syniti Data Quality is designed to manage and optimize data quality for diverse business needs. It provides robust analytics and insights, improving data consistency across enterprises. Its architecture supports seamless integration and scalability, making it suitable for complex data environments. Organizations can leverage it to streamline data governance, reduce operational costs, and foster better collaboration among teams. This platform is instrumental in fixing data inaccuracies, ensuring that only high-quality data is used to drive business strategies.

What are the key features of Syniti Data Quality?

Data Profiling: Provides in-depth analysis to identify data issues.
Data Cleansing: Automates the process of correcting data errors.
Data Matching: Removes duplicates to ensure unique records.
Monitoring and Alerts: Keeps track of data quality metrics with real-time alerts.
Data Enrichment: Enhances data with external sources for deeper insights.

What benefits can one expect when using Syniti Data Quality?

Improved Accuracy: Enhances data integrity, minimizing errors in processing.
Cost Efficiency: Reduces costs associated with data handling and error correction.
Enhanced Compliance: Ensures data aligns with regulatory standards.
Better Decision Making: Provides reliable data for strategic analysis.
Operational Efficiency: Streamlines processes across departments.

In industries like finance, Syniti Data Quality aids in compliance with stringent regulatory requirements, ensuring data accuracy and reliability. Healthcare sectors utilize it to maintain patient data integrity, improving service delivery. Retail businesses benefit from data consistency in inventory and customer management, driving improved customer experiences.

Syniti

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

Kraft Foods, Puget Sound Energy

Buyer's Guide

SAS Data Management vs. Syniti Data Quality

August 2026

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