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 8.4% mindshare in DQ, compared to Melissa’s 3.1% 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 6 Ataccama ONE Platform reviews

569 Views
170 Comparison Views

100% willing to recommend

Melissa Data Quality

Read 40 Melissa Data Quality reviews

403 Views
134 Comparison Views

95% willing to recommend

Ataccama ONE Platform

Melissa Data Quality

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 6, 2025

Melissa Data Quality and Ataccama ONE compete in the data accuracy and management sector. Ataccama ONE seems to have the upper hand due to its superior functionality tailored for complex data environments, whereas Melissa Data Quality offers cost-effective, straightforward solutions.

Features: Melissa Data Quality provides address verification, deduplication, and data enrichment capabilities. It easily integrates with various platforms, making it a convenient choice for quick deployment. Ataccama ONE excels with advanced data profiling, cleansing, and governance tools. It offers AI-driven insights, streamlining processes for users dealing with complex data sets.

Room for Improvement: Melissa Data Quality could enhance its AI capabilities to compete better in more complex environments and expand its profiling tools for comprehensive data handling. Increasing flexibility with integration beyond the current platforms could also be beneficial. Ataccama ONE might improve by simplifying its deployment process to make it more accessible and enhancing support for businesses requiring faster onboarding. Further refinement in user training materials could aid users in maximizing its advanced features.

Ease of Deployment and Customer Service: Melissa Data Quality is easy to deploy, with minimal integration time and robust, responsive customer support. Ataccama ONE offers a more intricate deployment that reflects its comprehensive features, requiring thorough user training. It provides extensive support options, crucial for leveraging its full range of tools.

Pricing and ROI: Melissa Data Quality is competitively priced, offering rapid ROI through cost-effective solutions suited to budget-conscious buyers. Ataccama ONE's higher pricing reflects its expansive capabilities and promises significant ROI by delivering extensive data governance impacts. It appeals to organizations looking to invest in a feature-rich data management platform.

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

Buyer's Guide

Ataccama ONE Platform vs. Melissa Data Quality

June 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

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

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Scrubbing Software (3rd)

Mindshare comparison

As of June 2025, in the Data Quality category, the mindshare of Ataccama ONE Platform is 8.4%, up from 3.0% compared to the previous year. The mindshare of Melissa Data Quality is 3.1%, up from 2.7% 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 drag-and-drop feature is incredibly flexible and straightforward."

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

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

"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."

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

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

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

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

"Allows us to identify cell phones before dialing, and giving us data about callers."

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

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

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

"Decreases chances of incorrect shipping addresses and, thus, returned packages."

"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."

More Melissa Data Quality pros

Cons

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

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

"Data movement is a pain."

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

"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."

"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.""

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

"It would be nice if it also had a user interface, as it did in years past."

"We are no longer using Melissa Data to clean up our address information as there are free tools that we can use to do the same thing."

"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."

"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."

"Needs to validate more addresses accurately."

"To continually update the database with NAICS codes on businesses."

More Melissa Data Quality cons

Pricing and Cost Advice

"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."

"The product is reasonably priced."

"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."

"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."

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

"It's affordable."

"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."

"Pricing is very reasonable."

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

"Melissa pricing is competitive."

More Melissa Data Quality pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

12%

Insurance Company

Manufacturing Company

Insurance Company

15%

Manufacturing Company

12%

Financial Services Firm

11%

Computer Software Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Microsoft Purview Data Governance vs Ataccama ONE Platform

Compared 22% of the time

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

Compared 20% of the time

Collibra Governance vs Ataccama ONE Platform

Compared 17% of the time

Profisee vs Ataccama ONE Platform

Compared 7% of the time

Alation Data Catalog vs Ataccama ONE Platform

Compared 6% of the time

More Ataccama ONE Platform Competitors

Experian Data Quality vs Melissa Data Quality

Compared 34% of the time

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

Compared 29% of the time

Precisely Trillium vs Melissa Data Quality

Compared 20% of the time

Talend Data Quality vs Melissa Data Quality

Compared 17% of the time

More Melissa Data Quality Competitors

Product Reports

Buyer's Guide

Ataccama ONE Platform

June 2025

Download Ataccama ONE Platform product report

Buyer's Guide

Melissa Data Quality

June 2025

Download Melissa Data Quality product report

Overview

Ataccama ONE Platform is a comprehensive data management and governance solution designed to address the challenges faced by organizations in managing and leveraging their data assets. Its primary use case is to enable organizations to gain control over their data, improve data quality, and ensure compliance with data regulations.

The most valuable functionality of Ataccama ONE includes data profiling, data quality management, data integration, master data management, and metadata management. These features allow organizations to understand the quality and structure of their data, integrate data from various sources, create a single view of their master data, and manage metadata to ensure data lineage and governance.

By leveraging Ataccama ONE, organizations can achieve several benefits. Firstly, it helps in improving data quality by identifying and resolving data issues, ensuring accurate and reliable data for decision-making. Secondly, it enables organizations to streamline data integration processes, reducing the time and effort required for data integration projects. Thirdly, it facilitates effective master data management, enabling organizations to have a consistent and accurate view of their critical data entities. Lastly, it helps organizations in complying with data regulations by providing data lineage, data privacy, and data governance capabilities.

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

June 2025

Free Report: Ataccama ONE Platform vs. Melissa Data Quality

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