Atlan vs erwin Data Intelligence comparison

Atlan and Quest Software are both solutions in the Data Governance category. Atlan is ranked #12 with an average rating of 8.1, while Quest Software is ranked #16 with an average rating of 8.0. Atlan holds a 2.1% mindshare in DG, compared to Quest Software’s 1.9% mindshare. Additionally, 100% of Atlan users are willing to recommend the solution, compared to 100% of Quest Software users who would recommend it.

Atlan

Read 8 Atlan reviews

1,456 Views
1,427 Comparison Views

100% willing to recommend

erwin Data Intelligence

Read 19 erwin Data Intelligence reviews

2,788 Views
2,732 Comparison Views

100% willing to recommend

Atlan

erwin Data Intelligence

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Executive SummaryUpdated on Nov 23, 2025

Erwin Data Intelligence and Atlan compete in the data management category. Erwin appears to have an edge in automation capabilities while Atlan excels in ease of use and integration.

Features: Erwin offers powerful automation via scripts, a central data catalog supporting traceability, and robust lineage features for standardization. It ensures process integration and reduced time to market. Atlan boasts a user-friendly interface with out-of-the-box connectors, seamless integration enhancing data lineage, and features like ML-driven data classification.

Room for Improvement: Erwin's SDK and API need consistency enhancements in scripting. Its automation and user navigation could be more intuitive to ease the learning curve. Atlan could improve its workflows, report distribution, and governance features to handle larger datasets efficiently.

Ease of Deployment and Customer Service: Erwin provides versatile deployment options for on-premises and cloud environments alongside responsive support with technical expertise. Atlan, with a cloud focus, receives praise for quick support and a flexible helpdesk system.

Pricing and ROI: Erwin's model includes per-user and server fees, offering competitive cost efficiency attributed to its automation capabilities. Atlan's per-user model is cost-effective for mid-sized organizations, albeit pricier than newer competitors.

To learn more, read our detailed Atlan vs. erwin Data Intelligence Report (Updated: December 2025).

Buyer's Guide

Atlan vs. erwin Data Intelligence

December 2025

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Helped 881,114 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

Atlan

Ranking in Data Governance

12th

Average Rating

8.2

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

Metadata Management (5th)

erwin Data Intelligence

Ranking in Data Governance

16th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

AI Governance (2nd)

Mindshare comparison

As of January 2026, in the Data Governance category, the mindshare of Atlan is 2.1%, up from 1.7% compared to the previous year. The mindshare of erwin Data Intelligence is 1.9%, down from 2.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Governance Market Share Distribution
Product	Market Share (%)
Atlan	2.1%
erwin Data Intelligence	1.9%
Other	96.0%

Data Governance

Featured Reviews

Peter Neumann

IT consultant at Pathfinder

Has struggled to meet business needs but supports technical data exploration and transparency

Atlan can be improved by concentrating more on business data since it is developed from developers for developers, and it needs to be more business relevant. For instance, when re-importing data model diagrams, Atlan provides some diagram automation that is not connected to the business glossary, which I consider a significant fault. Atlan needs to improve by focusing more on the business side of data, not only on technical aspects.If you want to focus on technical considerations, it would be beneficial to have an interface with a real business data modeling tool such as Erwin or other business data tools, since data modeling is not the same as Draw.io. Additionally, Atlan can improve its workflows, which are hard to understand. Working with templates, Excel import, export, and running automations is not self-explanatory, and you always need help from Atlan support team. If business people want to use it and run their own reports, it must be easier to customize for their business needs.

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Jog Raj

Senior Consultant at a computer software company with 11-50 employees

Automated lineage and business glossaries have improved data understanding and collaboration

I am open to answering a few questions about erwin Data Intelligence and sharing my opinion about the product. Regarding the analytic part of the product, I find it very interesting that erwin Data Intelligence has its own inbuilt reporting toolset, with a new version coming out in January that will be AI-powered. This means you will be able to write analytical reports and questions based on the metadata and data lineage, making it more powerful than the current version, as AI will assist in creating those reports and performing analysis on the metadata. I find that the time taken to realize value from erwin Data Intelligence can be quite long. Creating a data catalog and developing data lineage takes significant time, and I expect that AI will help accelerate the process of creating data products by streamlining the steps involved. I can recommend erwin Data Intelligence to other users. I would rate this review as an eight out of ten overall.

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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

"They also offer automated lineage embedded in the connectors, allowing us to track where the data is coming from and where it's going. We find it very efficient in cataloging data sources. Additionally, the user-friendly interface is a big plus, making it easy for users to familiarize themselves with the solution. These two features, in my opinion, stand out the most."

"The technical support services are good."

"Atlas is quite intuitive."

"Overall, I rate Atlan as a ten out of ten."

"The interfaces and automated imports have helped me with transparency, as we have different sources from different techniques such as DBT, Snowflake, and other regular databases, making it effective to connect these sources and navigate through them, filter them, and enrich the data with additional meter information."

"Overall, I rate Atlan a nine out of ten."

"Atlan is helpful for identifying datasets and discovering PI data, such as the classification levels of datasets (gold, silver, bronze)."

"As a senior analytics engineer, Atlan's ability to show end-to-end data lineage is the most important feature for me."

More Atlan pros

"The solution saves time in data discovery and understanding our entire organization's data."

"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."

"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."

"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."

"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 biggest benefit with erwin DI is that I have a single source of truth that I can send anybody to. If anybody doesn't know the answer we can go back to it. Just having a central location of business rules is good."

"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."

"It is a central place for everybody to start any ETL data pipeline builds. This tool is being heavily used, plus it's heavily integrated with all the ETL data pipeline design and build processes. Nobody can bypass these processes and do something without going through this tool."

More erwin Data Intelligence pros

Cons

"Working with templates, Excel import, export, and running automations is not self-explanatory, and you always need help from Atlan support team."

"The challenge is in the lineage, where it requires improvement."

"Certain UI changes could make Atlan more user-friendly."

"One area that could be improved is the capability to find duplicates of datasets."

"There are some improvements. There is a feature called Playbooks, which basically allows me to automate certain activities that would otherwise be manual. It's a very interesting feature, but there is room to improve it because, depending on the task you automate, the playbooks seem to have a hard time handling the task. So, it could be improved there. Even though it's a great feature, it can evolve further."

"Certain UI changes could make Atlan more user-friendly."

"One of the main areas for improvement is its governance capabilities. Atlan supports only basic out-of-the-box workflows, and it becomes challenging to customize features like how data owners should approve access to data assets."

"One of the main areas for improvement is its governance capabilities."

More Atlan cons

"The versioning can sometimes be confusing because we use the publishing feature for the mapping. Technical analysts sometimes have two versions, and they should know that the public version is the correct one."

"The technical support could be improved."

"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."

"If we are talking about the business side of the product, maybe the Data Literacy could be made a bit simpler. You have to put your hands on it, so there is room for improvement."

"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."

"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."

"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 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."

More erwin Data Intelligence cons

Pricing and Cost Advice

"We pay per-user license. It's a different classification model than with other solutions, where they usually charge you for resources. So, that was a better model for us. And because of this difference in models or classification, it was cheaper for us to go with Atlan."

"The price is reasonable, and a subscription is required."

"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 was at a good price. The federal government wouldn't buy something if the pricing wasn't good."

"The licensing cost is around $7,000 for user. This is an estimation."

"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."

"The solution is aggressively priced."

More erwin Data Intelligence pricing and cost advice

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Top Industries

By visitors reading reviews

Manufacturing Company

15%

Financial Services Firm

10%

Computer Software Company

Insurance Company

Financial Services Firm

14%

Government

10%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	1
Midsize Enterprise	1
Large Enterprise	7

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	4
Large Enterprise	14

Questions from the Community

What is your experience regarding pricing and costs for Atlan?

Atlas is competitively priced compared to other data governance platforms like Collibra and Informatica. The only major drawback is its lack of an integrated data quality module.

See all answers

What needs improvement with Atlan?

Atlan can be improved by integrating agents that can support users in finding assets of interest.

See all answers

What is your primary use case for Atlan?

Atlan is used as a data catalog and a data governance tool. The primary idea for implementing Atlan for data cataloging in day-to-day work was to create a business data catalog to support asset dis...

See all answers

What needs improvement with erwin Data Intelligence by Quest?

The dashboard in erwin Data Intelligence is customizable, and you can easily create different views. However, you are confined to the widgets that are already provided, so the customization is some...

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What is your primary use case for erwin Data Intelligence by Quest?

erwin Data Intelligence serves two primary use cases: one is where people use it as a data catalog, which is one of the main ones, and the other is for traceability and lineage.

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What advice do you have for others considering erwin Data Intelligence by Quest?

See all answers

Comparisons

Microsoft Purview Data Governance vs Atlan

Compared 37% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Atlan

Compared 16% of the time

Alation Data Catalog vs Atlan

Compared 12% of the time

Collibra Platform vs Atlan

Compared 9% of the time

Varonis Platform vs Atlan

Compared 5% of the time

More Atlan Competitors

Collibra Platform vs erwin Data Intelligence

Compared 25% of the time

Microsoft Purview Data Governance vs erwin Data Intelligence

Compared 21% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs erwin Data Intelligence

Compared 10% of the time

Alation Data Catalog vs erwin Data Intelligence

Compared 10% of the time

Microsoft Purview Data Lifecycle Management vs erwin Data Intelligence

Compared 6% of the time

More erwin Data Intelligence Competitors

Product Reports

Buyer's Guide

Atlan

January 2026

Download Atlan product report

Buyer's Guide

erwin Data Intelligence

January 2026

Download erwin Data Intelligence product report

Also Known As

No data available

erwin DG, erwin Data Governance

Overview

Atlan is a comprehensive data management platform designed to enhance data democratization, governance, and collaboration across departments in organizations. It offers a centralized data catalog, intuitive user interface, and robust governance framework to ensure data security and compliance. Users appreciate its efficiency in streamlining processes, promoting better communication, and providing insightful analytics, which drive organizational growth and success.

Atlan

Erwin Data Intelligence drives automation, supports data catalog and literacy, and offers Smart Data Connectors for efficient metadata handling. Its customization flexibility and integration facilitate enhanced data governance, visualization, analysis, and compliance.

Erwin Data Intelligence offers automation scripts that accelerate development, integrated data cataloging, data profiling, and lineage analysis to streamline information management. Users appreciate its capability in metadata harvesting, code engineering, and infrastructure integration. The tool provides flexibility to enhance governance and data visualization. While it performs well, users have noted challenges with API robustness and interface complexity, and there are opportunities to improve workflow integration, AI features, and large dataset handling. Companies rely on it for metadata management, automation of metadata mappings, and data governance to support compliance and literacy.

What are the main features of Erwin Data Intelligence?

Automation Scripts: Speeds up development processes through powerful scripts.
Data Catalog: Supports comprehensive data mapping and profiles for better analysis.
Smart Data Connectors: Efficiently handles code engineering and metadata harvesting.
Customization Flexibility: Adapts to existing infrastructure for seamless integration.
Comprehensive Visualization: Empowers data visualization and standardization processes.

What benefits and ROI can users expect?

Increased Development Speed: Automation scripts notably enhance development efficiency.
Improved Data Governance: Streamlines processes, supporting compliance and business definitions.
Effective Integration: Seamlessly fits with ETL tools and existing workflows.
Enhanced Data Literacy: Supports data literacy initiatives with robust cataloging features.
Comprehensive Impact Analysis: Facilitates thorough analysis for informed decision-making.

In industries such as finance, healthcare, and retail, organizations implement Erwin Data Intelligence for efficient metadata management and governance. It assists in automating lineage and mapping, supporting ETL procedures while enhancing compliance and data literacy efforts. Its flexibility and integration support create valuable data insights and governance improvements.

Quest Software

Sample Customers

Information Not Available

Oracle, Infosys, GSK, Toyota Motor Sales, HSBC

Buyer's Guide

Atlan vs. erwin Data Intelligence

December 2025

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