Melissa Data Quality vs SAS Data Management comparison

Melissa and SAS are both solutions in the Data Quality category. Melissa is ranked #8 with an average rating of 9.0, while SAS is ranked #11 with an average rating of 7.5. Melissa holds a 3.0% mindshare in DQ, compared to SAS’s 2.5% mindshare. Additionally, 95% of Melissa users are willing to recommend the solution, compared to 87% of SAS users who would recommend it.

Melissa Data Quality

Read 40 Melissa Data Quality reviews

436 Views
229 Comparison Views

95% willing to recommend

SAS Data Management

Read 17 SAS Data Management reviews

211 Views
175 Comparison Views

87% willing to recommend

Melissa Data Quality

SAS Data Management

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 6, 2025

SAS Data Management and Melissa Data Quality compete in the data management and quality sector. Melissa Data Quality is often regarded as superior due to its feature robustness, despite SAS's strong support and pricing.

Features: SAS Data Management provides robust data integration, powerful analytics tools, and strong governance capabilities. Melissa Data Quality focuses on data verification, enrichment, and cleansing, offering advanced data cleansing features.

Room for Improvement: SAS Data Management could enhance user interface intuitiveness, expand cloud compatibility, and streamline complex customization options. Melissa Data Quality could benefit from a wider range of integration options, enhanced real-time processing, and more comprehensive support for international data standards.

Ease of Deployment and Customer Service: SAS Data Management offers comprehensive deployment options with responsive customer support, ensuring a seamless setup process. Melissa Data Quality emphasizes streamlined deployment and efficient customer service, providing ease and quick access to support.

Pricing and ROI: SAS Data Management involves higher initial costs but offers significant ROI through its broad functionalities. Melissa Data Quality generally has a lower entry cost with quick ROI due to its focused data quality improvements, making it cost-effective for many businesses.

To learn more, read our detailed Melissa Data Quality vs. SAS Data Management Report (Updated: April 2025).

Buyer's Guide

Melissa Data Quality 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

Melissa Data Quality

Ranking in Data Quality

8th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Scrubbing Software (4th)

SAS Data Management

Ranking in Data Quality

11th

Average Rating

8.4

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (35th), Data Governance (26th)

Mindshare comparison

As of May 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 3.0%, up from 2.9% compared to the previous year. The mindshare of SAS Data Management is 2.5%, up from 2.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

GaryM

Data Architect at World Vision

SSIS MatchUp Component is Amazing

- Scalability is a limitation as it is single threaded. You can bypass this limitation by partitioning your data (say by alphabetic ranges) into multiple dataflows but even within a single dataflow the tool starts to really bog down if you are doing survivorship on a lot of columns. It's just very old technology written that's starting to show its age since it's been fundamentally the same for many years. To stay relavent they will need to replace it with either ADF or SSIS-IR compliant version. - Licensing could be greatly simplified. As soon as a license expires (which is specific to each server) the product stops functioning without prior notice and requires a new license by contacting the vendor. And updating the license is overly complicated. - The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation but that isn't true since pretty much all SSIS components are resizable except theirs! This is just an annoyance but needless impact on productivity when developing new data flows. - The tool needs to provide for incremental matching using the MatchUp for SSIS tool (they provide this for other solutions such as standalone tool and MatchUp web service). We had to code our own incremental logic to work around this. - Tool needs ability to sort mapped columns in the GUI when using advanced survivorship (only allowed when not using column-level survivorship). - It should provide an option for a procedural language (such as C# or VB) for survivor-ship expressions rather than relying on SSIS expression language. - It should provide a more sophisticated ability to concatenate groups of data fields into common blocks of data for advanced survivor-ship prioritization (we do most of this in SQL prior to feeding the data to the tool). - It should provide the ability to only do survivor-ship with no matching (matching is currently required when running data through the tool). - Tool should provide a component similar to BDD to enable the ability to split into multiple thread matches based on data partitions for matching and survivor-ship rather than requiring custom coding a parallel capable solution. We broke down customer data by first letter of last name into ranges of last names so we could run parallel data flows. - Documentation needs to be provided that is specific to MatchUp for SSIS. Most of their wiki pages were written for the web service API MatchUp Object rather than the SSIS component. - They need to update their wiki site documentation as much of it is not kept current. Its also very very basic offering very little in terms of guidelines. For example, the tool is single-threaded so getting great performance requires running multiple parallel data flows or BDD in a data flow which you can figure out on your own but many SSIS practitioners aren't familiar with those techniques. - The tool can hang or crash on rare occasions for unknown reason. Restarting the package resolves the problem. I suspect they have something to do with running on VM (vendor doesn't recommend running on VM) but have no evidence to support it. When it crashes it creates dump file with just vague message saying the executable stopped running.

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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

"I was able to dedupe millions of records in the past, and append the most recent email."

"We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database."

"Be confident that the scalability and load are not going to be an issue with the services. "

"Through more accurate data, our marketing department has been able to increase delivery and conversion rates through email direct marketing initiatives."

"Address parsing. Our other software does not have this functionality."

"By using Melissa Data, we are able to scrub and verify, then better validate the end customer's address to ensure a more consistent delivery of products."

"Initial setup was fairly straightforward. The documentation was very good in terms of how to integrate and consume the service(s) that we use. It did not take an abundance of time to set up things on our side to use the service."

"Ability to validate addresses, make corrections to address."

More Melissa Data Quality pros

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

"I find the solution to be very stable."

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

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

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

"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."

"The technical support is excellent."

"This is an established product with powerful data analysis and varied options for user entry points."

More SAS Data Management pros

Cons

"Pricing model."

"It would be helpful if a list of the codes and explanations could be included."

"Pricing is based on tiers, with each tier capped at a specified number of records processed. Once you go over the cap at one tier, you are automatically bumped to the next tier. However, they seem to count failed batch processes so it’s good to keep track of the number of records sent. They’ll fix the count when notified, but their system fails to detect actual successful processes versus failed processes."

"Address validation and parsing in a few countries have room for improvement."

"Tech support at Melissa Data was very quick to wash their hands of an issue and say it's IT policies on my side that are causing the issue. There was no offer to try and find a work-around. Just an overwhelming attitude of "it’s not our problem.""

"If I had multiple Excel files open and ran Listware it would crash Excel, charge the credits, and not save the results."

"The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation however all SSIS components are resizable so that isn't true. This is just an annoyance but needless."

"An area for improvement is where an end customer's address is not found in the Melissa Data database, even though it is a valid address."

More Melissa Data Quality cons

"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."

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

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

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

"Integration and cloud migration are areas where we see potential for improvement."

"The solution could use better documentation."

"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."

More SAS Data Management cons

Pricing and Cost Advice

"The only complaint that I have towards it is they sell licenses based on a range of usage, and I feel those ranges are too large."

"NCOA address verification was a requirement from USPS to send out the mailers. This was the only option that charged per address which was extremely helpful since we are a small non-profit school."

"The price for address validation is similar in all software. However, the price for geocoding decides the actual pricing. If you get their most accurate geocoding (called GeoPoints), then it will add about $10k+ per million requests."

"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."

"Cloud version is very cheap. On-premise version is expensive."

"Buy a lot more credits than you think you’re going to need."

"Melissa pricing is competitive."

"Generally, the cost is ROI positive, depending on your shipping volume."

More Melissa Data Quality 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 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

Insurance Company

15%

Manufacturing Company

12%

Financial Services Firm

11%

Computer Software Company

10%

Financial Services Firm

30%

Computer Software Company

13%

Insurance Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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What do you like most about SAS Data Management?

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

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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.

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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

Experian Data Quality vs Melissa Data Quality

Compared 34% of the time

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

Compared 28% of the time

Runner Technologies Data Quality vs Melissa Data Quality

Compared 19% of the time

Precisely Trillium vs Melissa Data Quality

Compared 19% of the time

More Melissa Data Quality Competitors

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

Compared 20% of the time

Palantir Foundry vs SAS Data Management

Compared 17% of the time

Informatica PowerCenter vs SAS Data Management

Compared 14% of the time

Collibra Governance vs SAS Data Management

Compared 12% of the time

Ab Initio Co>Operating System vs SAS Data Management

Compared 10% of the time

More SAS Data Management Competitors

Product Reports

Buyer's Guide

Melissa Data Quality

April 2025

Download Melissa Data Quality product report

Buyer's Guide

SAS Data Management

April 2025

Download SAS Data Management product report

Also Known As

No data available

SAS Data Management Platform, Data Management Platform, DataFlux

Overview

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Melissa

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

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.

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

Melissa Data Quality vs. SAS Data Management

April 2025

Free Report: Melissa Data Quality vs. SAS Data Management

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