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AtScale Adaptive Analytics (A3) vs erwin Data Intelligence by Quest comparison

 

Comparison Buyer's Guide

Executive Summary

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

AtScale Adaptive Analytics ...
Ranking in Data Governance
34th
Average Rating
5.0
Number of Reviews
1
Ranking in other categories
Data Virtualization (4th), BI (Business Intelligence) Tools (37th), BI on Hadoop (7th)
erwin Data Intelligence by ...
Ranking in Data Governance
9th
Average Rating
8.6
Reviews Sentiment
7.4
Number of Reviews
18
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Data Governance category, the mindshare of AtScale Adaptive Analytics (A3) is 0.3%, up from 0.3% compared to the previous year. The mindshare of erwin Data Intelligence by Quest is 2.1%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Governance
 

Featured Reviews

it_user822762 - PeerSpot reviewer
The GUI interface is nice and easy to use, but the organization of the icons is not saved across users
Connecting to a Hadoop database to create a cube to connect to Tableau. We want to be able to easily create cubes which can be connected to Tableau for visualization The product had many issues. We had great collaboration with the product development team, but the product was not able to meet our…
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

"The GUI interface is nice and easy to use."
"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."
"The biggest impact for us is that erwin generates DDL extremely quickly. We're able to pull in metadata, map it to a target, generate DDL to create the tables, and generate SSIS packages. Previously, especially going back 10 to 15 years ago, hundreds of hours had to be spent to manually perform these tasks. This solution completely automates it and gets it 90% done. We can then pass it off to a developer to create the items in SSIS."
"Data Intelligence has provided more profound insights into legacy data movements, lineages, and definitions in the short term. We have linked three critical layers of data, providing us with an end-to-end lineage at the column level."
"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."
"There is a wide range of widgets that enables the user to find the proper information quickly. The presentation of information is something very valuable."
"The possibility to write automation scripts is the biggest benefit for us. We have several products with metadata and metadata mapping capabilities. The big difference when we were choosing this product was the ability to run automation scripts against metadata and metadata mappings. Right now, we have a very high level of automation based on these automation scripts, so it's really the core feature for us."
"Data Intelligence creates a single source of truth for all of our metadata. This solution is better for data warehousing, but the metadata features speed up our development work. It's easy to create and manage mappings because we can export them to Informatica and pick up the work where we left off."
"Overall, DI's data cataloging, data literacy, and automation have helped our decision-makers because when a source wants to change something, we immediately know what the impact is going to be downstream."
 

Cons

"There was an issue with the incremental aggregation not working as indicated."
"The organization of the icons is not saved across users."
"The product was not able to meet our 10 second refresh requirements."
"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 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."
"One big improvement we would like to see would be the workflow integration of codeset mapping with the erwin source to target mapping. That's a bit clunky for us. The two often seem to be in conflict with one another. Codeset mappings that are used within the source to target mappings are difficult to manage because they get locked."
"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."
"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."
"The data quality assessment requires third-party components and a separate license."
"The SDK behind this entire product needs improvement. The company really should focus more on this because we were finding some inconsistencies on the LDK level. Everything worked fine from the UI perspective, but when we started doing some deep automation scripts going through multiple API calls inside the tool, then only some pieces of it work or it would not return the exact data it was supposed to do."
"There are a lot of little things like moving between read screens and edit screens. Those little human interface type of programming pieces will need to mature a bit to make it easier to get to where you want to go to put the stuff in."
 

Pricing and Cost Advice

Information not available
"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."
"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 price is reasonable and competitive. When you get into forward and reverse-engineering, the cost could go up. However, if you are a large organization, you would probably be able to access different packages. If, however, you don't need forward and reverse-engineering, then the price is relatively cheap."
"erwin was at a good price. The federal government wouldn't buy something if the pricing wasn't good."
"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 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."
"There is an additional fee for the server maintenance."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Manufacturing Company
12%
Computer Software Company
10%
Healthcare Company
8%
Computer Software Company
21%
Financial Services Firm
13%
Government
9%
Non Profit
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

Ask a question
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What do you like most about erwin Data Intelligence by Quest?
The data mapping manager is the most valuable feature.
What needs improvement with erwin Data Intelligence by Quest?
The data quality assessment requires third-party components and a separate license. I would like to have better integration around the data quality. I would appreciate the inclusion of a non-struct...
 

Also Known As

AtScale, AtScale Intelligence Platform
erwin DG, erwin Data Governance
 

Overview

 

Sample Customers

Rakuten, TD Bank, Aetna, Glaxo-Smith Kline, Biogen, Toyota, Tyson
Oracle, Infosys, GSK, Toyota Motor Sales, HSBC
Find out what your peers are saying about Microsoft, Informatica, Collibra and others in Data Governance. Updated: March 2025.
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