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Ataccama ONE Platform vs erwin Data Intelligence comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Aug 19, 2025

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 Governance
11th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
10
Ranking in other categories
Data Quality (4th), Data Scrubbing Software (3rd), Master Data Management (MDM) Software (4th)
erwin Data Intelligence
Ranking in Data Governance
28th
Average Rating
8.6
Reviews Sentiment
7.4
Number of Reviews
18
Ranking in other categories
AI Governance (17th)
 

Mindshare comparison

As of October 2025, in the Data Governance category, the mindshare of Ataccama ONE Platform is 2.3%, up from 2.2% compared to the previous year. The mindshare of erwin Data Intelligence is 1.8%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Governance Market Share Distribution
ProductMarket Share (%)
Ataccama ONE Platform2.3%
erwin Data Intelligence1.8%
Other95.9%
Data Governance
 

Featured Reviews

JohnZacharkan - PeerSpot reviewer
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.
Roy Pollack - PeerSpot reviewer
The solution provides more profound insights into legacy data movements, lineages, and definitions in the short term.
We have loaded over 300,000 attributes and more than 1000 mappings. The performance is slow, depending on the lineage or search. This is supposed to be fixed in the later versions, but we haven't upgraded yet. The integration with various metadata sources, including erwin Data Modeler, isn't smooth in the current version. It took some experimentation to get things working. We hope this is improved in the newer version. The initial version we used felt awkward because Erwin implemented features from other companies into their offering.

Quotes from Members

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

Pros

"Customer service was excellent, and I would give it a ten out of ten."
"It is also easy to deploy."
"The product’s important feature is data profiling and quality check."
"The data profile itself is excellent. You can understand the quality of the data in layman's terms."
"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 notable aspect lies in the workflow structure, where building the workflow aligns significantly with data governance."
"The ease of use of the user console is valuable."
"The drag-and-drop feature is incredibly flexible and straightforward."
"The data mapping manager is the most valuable feature."
"erwin has tremendous capabilities to map right from the business technologies to the endpoint, such as physical entities and physical attributes, from a lineage standpoint."
"They have just the most marvelous reports called mind maps, where whatever you are focused on sits in the middle. They have this wonderful graphic spiderweb that spreads out from there where you can see this thing mapped to other logical bits or physical bits and who's the steward of it. It's very cool and available to your business teams through a portal."
"We use the codeset mapping quite a bit to match value pairs to use within the conversion as well. Those value pair mappings come in quite handy and are utilized quite extensively. They then feed into the automation of the source data extraction, like the source data mapping of the source data extraction, the code development, forward engineering using the ODI connector for the forward automation."
"The data management is, obviously, key in understanding where the data is and what the data is. And the governance can be done at multiple levels. You have the governance of the code sets versus the governance of the business terms and the definitions of those business terms. You have the governance of the business data models and how those business data models are driving the physical implementation of the actual databases. And, of course, you have the governance of the mapping to make sure that source-to-target mapping is done and is being shared across the company."
"Being able to capture different business metrics and organize them in different catalogs is most valuable. We can organize these metrics into sales-related metrics, customer-related metrics, supply chain-related metrics, etc."
"We always know where our data is, and anybody can look that up, whether they're a business person who doesn't know anything about Informatica, or a developer who knows everything about creating data movement jobs in Informatica, but who does not understand the business terminology or the data that is being used in the tool."
"The solution gives us data lineage which means we can see an impact if we make a change. The ability for us to have that in this company is brilliant because we used to have 49 data stewards from some 23 different groups within six major departments. Each one of those was a silo unto itself. The ability to have different glossaries — but all pointed to the same key terms, key concepts, or key attributes — has made life really simple."
 

Cons

"They could focus more on marketing the product. The current marketing strategy is not working."
"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."
"There is a notable challenge in having to provide detailed filters before the site recognizes the search criteria."
"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."
"The interfacing to tools such as Collibra was somewhat cumbersome and required more thought."
"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."
"Data movement is a pain."
"We still need another layer of data quality assessments on the source to see if it is sending us the wrong data or if there are some issues with the source data. For those things, we need a rule-based data quality assessment or scoring where we can assess tools or other technology stacks. We need to be able to leverage where the business comes in, defining some business rules and have the ability to execute those rules, then score the data quality of all those attributes. Data quality is definitely not what we are leveraging from this tool, as of today."
"Really huge datasets, where the logical names or the lexicons weren't groomed or maintained well, were the only area where it really had room for improvement. A huge data set would cause erwin to crash. If there were half a million or 1 million tables, erwin would hang."
"The fact that I sometimes have to go in and out of different applications, even though it's all part of the whole erwin suite, perhaps means it could be architected a little bit better. I think they do have some ideas for improvements there."
"There may be some opportunities for improvement in terms of the user interface to make it a little bit more intuitive. They have made some good progress. Originally, when we started, we were on version 9 or 10. Over the last couple of releases, I've seen some improvements that they have made, but there might be a few other additional areas in UI where they can make some enhancements."
"It's a little bit clunky. I think a lot of these features were bolted on, and they don't necessarily transition smoothly in the interface. I would like to see a little more cohesion."
"The technical support could be improved."
"Everything about Data Intelligence is complex. Though we've used the tool for five years, we're still only using about 30 to 40 percent of its capabilities. It would be helpful if we could customize and simplify the user interface because there are so many redundant things."
"There was a huge learning curve, and I'd been in software development for most of my career. The application itself, and how it runs menus and screens when you can modify and code, is complex. I have found that kind of cumbersome."
 

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."
"The product is reasonably priced."
"There is no need to buy a license. You can just download it and use it for free."
"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."
"Smart Data Connectors have some costs, and then there are user-based licenses. We spend roughly $150,000 per year on the solution. It is a yearly subscription license that basically includes the cost for Smart Data Connectors and user-based licenses. We have around 30 data stewards who maintain definitions, and then we have five IT users who basically maintain the overall solution. It is not a SaaS kind of operation, and there is an infrastructure cost to host this solution, which is our regular AWS hosting cost."
"The licensing cost was very affordable at the time of purchase. It has since been taken over by erwin, then Quest. The tool has gotten a bit more costly, but they are adding more features very quickly."
"The price is too high."
"There is an additional fee for the server maintenance."
"The whole suite, not just the DI but the modeling software, the harvester, Mapping Manager — everything we have — is about $100,000 a year for our renewals. That works out to each module being something like $8,000 to $10,000."
"erwin's pricing was cheaper than its competitors."
"You buy a seat license for your portal. We have 100 seats for the portal, then you buy just the development licenses for the people who are going to put the data in."
"erwin is cheaper than other solutions and this should appeal to other buyers. It has a good price tag."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
10%
Computer Software Company
9%
Insurance Company
9%
Computer Software Company
26%
Financial Services Firm
11%
Government
7%
Non Profit
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Large Enterprise7
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise4
Large Enterprise14
 

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.
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...
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...
Ask a question
Earn 20 points
 

Also Known As

Ataccama DQ Analyzer
erwin DG, erwin Data Governance
 

Overview

 

Sample Customers

Société Générale, First Data, Raiffeisenbank International, T-Mobile, Avast, RSA, Toronto Public Library
Oracle, Infosys, GSK, Toyota Motor Sales, HSBC
Find out what your peers are saying about Ataccama ONE Platform vs. erwin Data Intelligence and other solutions. Updated: September 2025.
868,787 professionals have used our research since 2012.