Ataccama DQ Analyzer vs Melissa Data Quality comparison

Ataccama and Melissa are both solutions in the Data Scrubbing Software category. Ataccama is ranked #6, while Melissa is ranked #4 with an average rating of 9.0. Ataccama holds a 5.7% mindshare in DSS, compared to Melissa’s 6.8% mindshare. Additionally, 100% of Ataccama users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

Ataccama DQ Analyzer

Read 4 Ataccama DQ Analyzer reviews

410 Views
226 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

306 Views
160 Comparison Views

95% willing to recommend

Ataccama DQ Analyzer

Melissa Data Quality

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Ataccama DQ Analyzer and Melissa Data Quality based on real PeerSpot user reviews.

Find out in this report how the two Data Scrubbing Software solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Ataccama DQ Analyzer vs. Melissa Data Quality Report (Updated: March 2025).

Buyer's Guide

Ataccama DQ Analyzer vs. Melissa Data Quality

March 2025

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Helped 845,406 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

Ataccama DQ Analyzer

Ranking in Data Scrubbing Software

6th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Melissa Data Quality

Ranking in Data Scrubbing Software

4th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Quality (8th)

Mindshare comparison

As of April 2025, in the Data Scrubbing Software category, the mindshare of Ataccama DQ Analyzer is 5.7%, down from 9.9% compared to the previous year. The mindshare of Melissa Data Quality is 6.8%, up from 4.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Scrubbing Software

Featured Reviews

Chuha Adequatov

Head of Regulatory Reference Data Management Division at Altynalmas JSC

Is easy to deploy and is free, but marketing strategies need improvement

We use Ataccama DQ Analyzer to analyze data migration from one source to another. We use it to clean up the data I like that there is no need to buy a license. You can just download it and use it free. It is also easy to deploy. They could focus more on marketing the product. The current…

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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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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The data profile itself is excellent. You can understand the quality of the data in layman's terms."

"It is also easy to deploy."

"We like having the ability to write our own utilities/software to process our records and store the final output the way we want."

"We have only been using this for about two months, but it has sped up our processing significantly. It makes data mining easy and fast. We don't have to spend an entire month gathering correct information on leads. All we need is a list of home addresses, and in minutes we have names and phone numbers to increase our chance of these leads becoming customers."

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

"Ability to keep our data set clean and usable for our community searches."

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

"It cuts down significantly on time in trying to match names to addresses. I can do in a few hours what would otherwise take days to accomplish."

"SSIS integration."

"The customers' addresses are now complete, correct and follow one consistent format."

More Melissa Data Quality pros

Cons

"Although DQA can fetch data from most of the commonly used data sources, it has limited modifiers to get data, meaning that the number of technologies from which the data can be acquired is limited. For example, DQA does not support fetching data from Twitter or Facebook. Many competitors have this feature."

"They could focus more on marketing the product. The current marketing strategy is not working."

"More countries should be supported by Melissa."

"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."

"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."

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

"Needs to validate more addresses accurately."

"The SSIS component setup seems a little klunky."

"I wish there was a way to do a "test run" and see what a particular format will give you."

"One thing I would want to have, when you're doing a property search, you can do it either on the FIPS in the APN number or the address itself. For some entries, I'll have the APN number, and some I'll have the address. Apparently it cannot process something when both the FIPS-APN and the address are on there. I have to sort, once with one and once with the other, which is a little bit of a pain."

More Melissa Data Quality cons

Pricing and Cost Advice

"There is no need to buy a license. You can just download it and use it for free."

"Trial subscriptions (via cloud) are very cheap and easy to use. It’s a great way to test Listware to see if you want to go deeper with integration."

"This vendor has no equal in pricing for equivalent functionality."

"Understand how may transactions you will be processing so that you can get the right tier pricing."

"Depends on situation. We prefer to have data onsite, but some might prefer web access."

"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."

"Fully understand your volume, both monthly and annually. Speak with a Melissa account manager, they will put together an effective solution to meet your needs."

"It's affordable."

"You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Manufacturing Company

Energy/Utilities Company

Insurance Company

14%

Manufacturing Company

13%

Financial Services Firm

12%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Comparisons

Talend Data Quality vs Ataccama DQ Analyzer

Compared 71% of the time

Alteryx vs Ataccama DQ Analyzer

Compared 29% of the time

More Ataccama DQ Analyzer Competitors

Experian Data Quality vs Melissa Data Quality

Compared 41% of the time

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

Compared 35% of the time

Talend Data Quality vs Melissa Data Quality

Compared 24% of the time

More Melissa Data Quality Competitors

Product Reports

Buyer's Guide

Data Scrubbing Software

March 2025

Download Ataccama DQ Analyzer product report

Buyer's Guide

Melissa Data Quality

March 2025

Download Melissa Data Quality product report

Also Known As

DQ Analyzer

No data available

Overview

DQ Analyzer (DQA) combines advanced data profiling and analysis capabilities with a point-and-click interface that is simple enough for business managers to use without extensive training.

Ataccama

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

Sample Customers

University of Arizona

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

Buyer's Guide

Ataccama DQ Analyzer vs. Melissa Data Quality

March 2025

Free Report: Ataccama DQ Analyzer vs. Melissa Data Quality

Find out what your peers are saying about Ataccama DQ Analyzer vs. Melissa Data Quality and other solutions. Updated: March 2025.

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