Ataccama ONE Platform vs Melissa Data Quality comparison

Ataccama and Melissa are both solutions in the Data Quality category. Ataccama is ranked #4 with an average rating of 8.0, while Melissa is ranked #8 with an average rating of 9.0. Ataccama holds a 9.8% mindshare in DQ, compared to Melissa’s 3.2% mindshare. Additionally, 100% of Ataccama users are willing to recommend the solution, compared to 95% of Melissa users who would recommend it.

Ataccama ONE Platform

Read 10 Ataccama ONE Platform reviews

2,497 Views
949 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

653 Views
372 Comparison Views

95% willing to recommend

Ataccama ONE Platform

Melissa Data Quality

Comparison Buyer's Guide

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Executive SummaryUpdated on Aug 13, 2025

Melissa Data Quality and Ataccama ONE Platform compete in the data management category, focusing on data quality and governance. Melissa excels in affordable pricing and excellent support, while Ataccama stands out with its extensive features and enhanced value.

Features: Melissa Data Quality focuses on data cleansing, matching, and enrichment to improve data accuracy. Ataccama ONE Platform, however, provides robust data governance, comprehensive data discovery, and a unified platform for integrated data management. Melissa specializes in core data quality functions, whereas Ataccama offers a more extensive suite of tools for holistic data management.

Room for Improvement: Melissa could enhance its features by expanding its data governance capabilities and providing more comprehensive reporting tools. Additionally, increasing integration capabilities with enterprise systems and offering advanced analytics features would add value. Ataccama could improve by simplifying its initial setup process, offering more affordable pricing tiers for smaller organizations, and enhancing its user interface for ease of use.

Ease of Deployment and Customer Service: Melissa Data Quality is known for a straightforward deployment process, with responsive customer service facilitating quick integration. Ataccama ONE Platform offers advanced deployment options, though it may require more initial customization and setup time. Melissa's simpler setup appeals to those needing immediate implementation, while Ataccama's complexity benefits enterprises requiring detailed customization support.

Pricing and ROI: Melissa Data Quality generally offers a lower setup cost, appealing to smaller organizations or those with budget constraints. It achieves effective ROI through cost savings via enhanced data accuracy. In contrast, Ataccama ONE Platform demands a higher initial investment but provides significant ROI through its advanced features and capabilities, making it attractive for larger enterprises with comprehensive data strategy ambitions.

To learn more, read our detailed Ataccama ONE Platform vs. Melissa Data Quality Report (Updated: July 2025).

Buyer's Guide

Ataccama ONE Platform vs. Melissa Data Quality

July 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

Ataccama ONE Platform

Ranking in Data Quality

4th

Ranking in Data Scrubbing Software

2nd

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Master Data Management (MDM) Software (4th), Data Governance (11th)

Melissa Data Quality

Ranking in Data Quality

8th

Ranking in Data Scrubbing Software

4th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Data Quality category, the mindshare of Ataccama ONE Platform is 9.8%, up from 6.7% compared to the previous year. The mindshare of Melissa Data Quality is 3.2%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

JohnZacharkan

Senior Architect at SourcEdge

Enhanced data quality with machine learning support in diverse environments

We used Ataccama ONE to read data from the mainframe for a data quality perspective. There's a significant lack in that area with tools being able to interface with mainframe. MetLife has a diverse environment, including DB2, Oracle, SQL Server, legacy, and vSAN files. Being able to work in these various environments and put them to a single data quality tool was very appealing. Additionally, Ataccama supported AI and machine learning, which was one of the features I liked. Furthermore, we were able to interface bidirectionally with Collibra for data governance, catching data quality issues before propagating through the system.

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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 desktop version of the solution was particularly valuable to me, primarily for creating components. We opted for the data quality aspect to assess the quality of our data warehouse. The functionalities available allowed us to not only check data quality but also serve as an ETL tool. This versatility enabled data transformation and storage in various formats, including files on platforms like SharePoint or local online directories. The flexibility of the tool catered to the specific needs of those building components, contributing to our desired outcomes."

"It is also easy to deploy."

"Customer service was excellent, and I would give it a ten out of ten."

"The drag-and-drop feature is incredibly flexible and straightforward."

"The product’s important feature is data profiling and quality check."

"The ease of use of the user console is valuable."

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

"The notable aspect lies in the workflow structure, where building the workflow aligns significantly with data governance."

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

"This tool works better for us than using a batch processing system that we do not have enough control over as each record is being processed."

"SSIS integration."

"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."

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

"Provides simplicity, ease of use, combined with overall accuracy of data."

"It gives me an assessed value of the property in question. My partner and I are property investors, and it's good to get an assessed value to cull out properties that we're not interested in."

"We mainly communicate with our customers via email, so we primarily use it to find a phone number so we can contact them more efficiently. This allows us to talk to them and resolve their issues much more quickly."

More Melissa Data Quality pros

Cons

"The interfacing to tools such as Collibra was somewhat cumbersome and required more thought."

"Data movement is a pain."

"It is complicated to fetch 20-25 reports when we profile the data."

"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."

"I believe it would be beneficial if it could enhance its flexibility to connect with a wider range of downstream systems beyond just Excel and Postgres."

"Speaking specifically about the version we use, version 12.3, I'm unsure if this has been addressed in subsequent versions. One improvement I'd like to see pertains to the language used in certain components, especially in data quality checks. The language complexity posed a challenge for beginners. Although we had on-site assistance from Ataccama, making it manageable for us, some individuals found it difficult to comprehend, necessitating additional support. The provision of a comprehensive guide for on-premise installation can also be enhanced. The lack of detailed information on the solution's workings and the overwhelming nature of notifications, with extensive content, were areas of concern. Streamlining the notification content in newer versions would significantly expedite issue resolution."

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

"There is a notable challenge in having to provide detailed filters before the site recognizes the search criteria."

"Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines."

"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."

"There are some companies out there using Google or other sources to check / confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."

"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."

"MatchUp seems to be single threaded, and limits the amount of data that can be processed automatically."

"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.""

"The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed"

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."

"The product is reasonably priced."

"Despite not being extremely low-cost, the pricing appears reasonable, making it a profitable and viable choice for companies that prioritize data security and adhere to specific policies."

"Our licensing model wasn't user-specific; instead, we paid fees for the engine and maintenance. As we didn't have a support contract, maintenance fees were likely nonexistent. Regarding the upgrade, we had an account for the initial two or three years, and considering the features provided by the solution, the pricing was reasonable."

"They were willing to work with our preferred vendors, though it involved extra steps to get the license."

"It's affordable."

"Pricing is very reasonable."

"We are concerned that our own pricing is going up every year for Melissa Data products, but we highly recommend the services for people who are routinely sending out mailings."

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

"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."

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

"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."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Manufacturing Company

10%

Computer Software Company

Insurance Company

14%

Manufacturing Company

11%

Financial Services Firm

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Ataccama ONE Platform?

The notable aspect lies in the workflow structure, where building the workflow aligns significantly with data governance.

See all answers

What needs improvement with Ataccama ONE Platform?

The interfacing to tools such as Collibra was somewhat cumbersome and required more thought. While it was possible to configure these interfaces, they required some coding. It would be beneficial i...

See all answers

What is your primary use case for Ataccama ONE Platform?

Some of the use cases for Ataccama ONE included data quality, identifying and mapping to Collibra, which was their data governance tool. It was critical for them to interface directly with that too...

See all answers

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Comparisons

Informatica Intelligent Data Management Cloud (IDMC) vs Ataccama ONE Platform

Compared 17% of the time

Microsoft Purview Data Governance vs Ataccama ONE Platform

Compared 17% of the time

Collibra Governance vs Ataccama ONE Platform

Compared 13% of the time

Talend Data Quality vs Ataccama ONE Platform

Compared 8% of the time

Profisee vs Ataccama ONE Platform

Compared 5% of the time

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Experian Data Quality vs Melissa Data Quality

Compared 19% of the time

Coheris Spad Data Quality vs Melissa Data Quality

Compared 17% of the time

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

Compared 17% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 17% of the time

Eprentise Data Quality vs Melissa Data Quality

Compared 10% of the time

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Product Reports

Buyer's Guide

Ataccama ONE Platform

August 2025

Download Ataccama ONE Platform product report

Buyer's Guide

Melissa Data Quality

August 2025

Download Melissa Data Quality product report

Also Known As

Ataccama DQ Analyzer

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Overview

Ataccama ONE Platform provides a comprehensive solution for profiling, cleansing, and integrating data with a user-friendly drag-and-drop interface, enhancing data quality and governance.

Ataccama ONE Platform enhances data profiling and cleansing with easy configuration and robust integration, such as with Collibra. Users value its drag-and-drop capabilities, supporting mainframe, AI, and machine learning. The platform improves data security through profiling and masking while offering extensive integration options. Some areas needing improvement include large database handling and batch management. Additional support for social media data sources, better documentation, and clearer language would be beneficial. Enhanced interfaces, particularly with Collibra, and refined notification systems are desired. This platform suits users seeking improvements in data quality, governance classification, and data migration, connecting with sources like Microsoft SQL, Oracle, and Teradata.

What are the key features of Ataccama ONE Platform?

Data Profiling and Cleansing: Enhances data quality with easy configuration.
Flexible Integration: Seamless integration with platforms like Collibra.
Drag-and-Drop Interface: Provides ease in workflow management.
Support for AI and Machine Learning: Offers advanced analytical capabilities.
Data Security: Ensures protection with profiling and masking features.

What benefits and ROI can users expect?

Improved Data Quality: Enhances data accuracy and reliability.
Enhanced Governance: Facilitates better metadata classification and compliance.
Increased Efficiency: Streamlines data integration and transformation processes.
Advanced Analytics: Leverages AI for insightful data analysis.

In industries like finance and healthcare, Ataccama ONE Platform facilitates data quality management and ensures compliance by connecting with data sources such as Microsoft SQL and Oracle. These industries utilize it for data migration tasks, ensuring data integrity through mapping and transformation processes.

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

Société Générale, First Data, Raiffeisenbank International, T-Mobile, Avast, RSA, Toronto Public Library

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 ONE Platform vs. Melissa Data Quality

July 2025

Free Report: Ataccama ONE Platform vs. Melissa Data Quality

Find out what your peers are saying about Ataccama ONE Platform vs. Melissa Data Quality and other solutions. Updated: July 2025.

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