Oracle Enterprise Data Quality (EDQ) vs SAS Data Management comparison

Oracle and SAS are both solutions in the Data Quality category. Oracle is ranked #16, while SAS is ranked #7 with an average rating of 9.0. Oracle holds a 2.8% mindshare in DQ, compared to SAS’s 3.3% mindshare. Additionally, 88% of Oracle users are willing to recommend the solution, compared to 88% of SAS users who would recommend it.

Oracle Enterprise Data Qual...

Read 8 Oracle Enterprise Data Quality (EDQ) reviews

543 Views
538 Comparison Views

88% willing to recommend

SAS Data Management

Read 18 SAS Data Management reviews

2,052 Views
451 Comparison Views

88% willing to recommend

Oracle Enterprise Data Qual...

SAS Data Management

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Executive SummaryUpdated on Dec 11, 2025

Oracle Enterprise Data Quality and SAS Data Management are both data management tools, catering to enterprises with varying needs. Oracle EDQ has an advantage in terms of pricing and customer support, whereas SAS Data Management is favored for its comprehensive analytics capabilities.

Features: Oracle EDQ is recognized for its efficient data cleansing, profiling, and matching, ensuring high data reliability. Its customizable platform integrates well with third-party applications. For SAS Data Management, key features include data integration and transformation, allowing extensive data handling, and robust monitoring capabilities that support complex data environments.

Room for Improvement: Oracle EDQ could enhance its analytics capabilities and data integration features to match SAS's level. The customization options and user interface can also be expanded. In terms of SAS Data Management, simplification of deployment processes and improvement in user-friendly features would benefit organizations seeking faster implementation. Cost efficiency and initial investment requirements are areas for potential enhancement.

Ease of Deployment and Customer Service: Oracle EDQ offers a straightforward deployment, with extensive customer support aiding rapid engagement with the system. SAS Data Management, though providing strong support, involves a more complex deployment due to its extensive feature set, benefiting those with sophisticated data needs but requiring a greater time commitment.

Pricing and ROI: Oracle EDQ is perceived as cost-effective, offering lower setup costs and faster ROI through simpler deployment. SAS Data Management might require a higher upfront investment, yet offers significant returns via its comprehensive data management features, proving beneficial for long-term analytic objectives.

To learn more, read our detailed Oracle Enterprise Data Quality (EDQ) vs. SAS Data Management Report (Updated: December 2025).

Buyer's Guide

Oracle Enterprise Data Quality (EDQ) vs. SAS Data Management

December 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

Oracle Enterprise Data Qual...

Ranking in Data Quality

16th

Average Rating

8.4

Reviews Sentiment

7.9

Number of Reviews

Ranking in other categories

No ranking in other categories

SAS Data Management

Ranking in Data Quality

7th

Average Rating

8.6

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Integration (28th), Data Governance (22nd)

Mindshare comparison

As of January 2026, in the Data Quality category, the mindshare of Oracle Enterprise Data Quality (EDQ) is 2.8%, up from 1.5% compared to the previous year. The mindshare of SAS Data Management is 3.3%, up from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Market Share Distribution
Product	Market Share (%)
SAS Data Management	3.3%
Oracle Enterprise Data Quality (EDQ)	2.8%
Other	93.9%

Data Quality

Featured Reviews

Venkatraman Bhat

Deliver Head - Database and Infrastructure Cloud Services at Tech Mahindra Limited

Fast, has good extraction, validation, and transformation features, and provides good support

Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution.

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Fernanda Knopki

Data Scientist & Scrum Master at Volvo Group

Has supported centralized data access and improved governance through unified administration

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. The data integration tools with SAS Data Management were quite good because they allowed me to do all lineage, to manage and see all the variables, find the libraries where the data is, and understand the data in just one tool. Offering another development environment combining code and predefined objects, where I could just drag and drop to achieve what I needed, although some objects were not too good, but some were effective. The metadata management feature of SAS Data Management helps a lot; creating your data marts or data lake with good naming conventions, library conventions, and so on is very important because it allows easy queries to find the whole structure, though I think metadata governance also depends on first definitions, not only on the tool. SAS Data Management is very good for data governance; for me, it was the best tool I worked with in data management, although I don't have too much experience with others, and it truly helped a lot.

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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 features I like most about Oracle Data Quality include extraction, transformation, and validation, which makes it a multipurpose product such as Oracle GoldenGate and Oracle Data Integrator. I also like that Oracle Data Quality is very fast, so you can use it for a large volume of data within a short period. You have to do the validation very quickly, so the solution helps in that area of data quality. Another feature of Oracle Data Quality that I like is the MDM (Master Data Management) where you'll have a single source of protection, and this makes the solution perfect and helpful to my company."

"With Oracle Data Quality, the most valuable feature is entity matching."

"Once it is set up, it is easy to use and maintain."

"I have found the most valuable features to be data cleansing and deduplication."

"I find the solution to be very stable."

"The data integration tools with SAS Data Management were quite good because they allowed me to do all lineage, to manage and see all the variables, find the libraries where the data is, and understand the data in just one tool."

"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."

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

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

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

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

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

More SAS Data Management pros

Cons

"Oracle Data Quality should integrate with data warehousing solutions such as Azure and CWS Office. For example, having the ability to integrate with tools, such as Azure Synapse and SQL data warehousing would be a great benefit."

"If the length of time required for deployment was reduced then it would be very helpful."

"Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution."

"Oracle is currently not that intuitive. We need to use programmers to write code for a lot of the procedures. We need to have them write CL SQL code and write a CL script."

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

"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."

"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."

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

"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."

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

"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."

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

More SAS Data Management cons

Pricing and Cost Advice

"The vendor needs to revisit their pricing strategy."

"The price of this solution is comparable to other similar solutions."

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

"The tool is a bit expensive."

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

28%

Government

Computer Software Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Midsize Enterprise	2
Large Enterprise	7

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	8

Questions from the Community

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

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

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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.

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What is your primary use case for SAS Data Management?

The main idea for using SAS Data Management was to bring all data inside SAS. I brought the finance area and the sales area in the company that I have worked, along with some market planning data, ...

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Comparisons

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Compared 35% of the time

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SAP Data Services vs Oracle Enterprise Data Quality (EDQ)

Compared 11% of the time

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Compared 11% of the time

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

Compared 15% of the time

Collibra Platform vs SAS Data Management

Compared 11% of the time

Qlik Talend Cloud vs SAS Data Management

Compared 6% of the time

Protegrity’s Data Protection Platform vs SAS Data Management

Compared 6% of the time

Palantir Foundry vs SAS Data Management

Compared 5% of the time

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Product Reports

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Data Quality

December 2025

Oracle Enterprise Data Quality (EDQ) report

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Buyer's Guide

SAS Data Management

December 2025

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Also Known As

Datanomic

SAS Data Management Platform, Data Management Platform, DataFlux

Overview

Oracle Enterprise Data Quality is a comprehensive tool for improving data integrity through address verification, profiling, cleansing, and synchronization.

Oracle Enterprise Data Quality empowers organizations to manage their data by ensuring integrity and consistency. It provides efficient address verification, data profiling, cleansing, and synchronization. With capabilities like entity matching, deduplication, extraction, transformation, and validation, it supports diverse data types to enhance data quality processes. While it is seamless in data matching and third-party app integration, the platform benefits organizations by supporting Master Data Management for consolidated data protection. However, improvements in documentation, ERP and warehouse integration, cloud and mobile support, and reduced deployment time could enhance the user experience. Pricing strategy and installation challenges, especially involving coding, need attention for broader accessibility.

What are the main features of Oracle Enterprise Data Quality?

Address Verification: Ensures accuracy in address data.
Data Profiling: Analyzes data characteristics for better insights.
Cleansing: Refines data by removing inaccuracies.
Data Synchronization: Aligns data across platforms effortlessly.
Entity Matching: Identifies and matches related entities.
Deduplication: Eliminates redundant data entries efficiently.
Transformation and Validation: Converts data to required formats, verifying its accuracy.

What benefits and ROI can users expect from Oracle Enterprise Data Quality?

Data Integrity: Maintains consistent data accuracy.
Reduced Redundancy: Minimizes duplicate data across systems.
Enhanced Data Governance: Strengthens data management strategies.
Improved Accuracy: Boosts the precision of data validation.
Efficient Data Processing: Accelerates data handling routines.

Industries like education find Oracle Enterprise Data Quality invaluable for systems such as university fundraising, where tracking donor contributions accurately is crucial. Used in data governance, it manages quality during ETVL processes ensuring high precision for data warehouses and Data Lakehouses.

Oracle

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

Roka Bioscience, Statistics Centre _ Abu Dhabi , Raymond James Financial inc., CaixaBank, Industrial Bank of Korea, Posco, NHS Business Services Authority, RWE Power, LIFE Financial Group,

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

Oracle Enterprise Data Quality (EDQ) vs. SAS Data Management

December 2025

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