Atlan vs Quest Data Intelligence comparison

Why PeerSpot?

Atlan and Quest Software are both solutions in the Data Governance category. Atlan is ranked #12 with an average rating of 8.3, while Quest Software is ranked #18 with an average rating of 8.0. Atlan holds a 1.8% mindshare in DG, compared to Quest Software’s 2.5% 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 10 Atlan reviews

2,884 Views
2,769 Comparison Views

100% willing to recommend

Quest Data Intelligence

Read 22 Quest Data Intelligence reviews

5,399 Views
4,265 Comparison Views

100% willing to recommend

Atlan

Quest Data Intelligence

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 16, 2026

Erwin Data Intelligence and Atlan compete in the data management solutions category. Erwin seems to have an advantage in centralized data management, while Atlan excels in automation and user-friendly interfaces.

Features: Erwin Data Intelligence integrates smart data connectors and metadata associations, providing a single source of truth and enhancing organizational efficiency. Its data lineage feature reduces silos and facilitates adaptation across enterprise environments. Atlan offers seamless integrations and extensive automation with an intuitive interface, which makes it easy for business users to adopt and manage metadata efficiently. Atlan’s automated data pipeline enhances data navigation and consolidation, making essential business processes smoother.

Room for Improvement: Erwin Data Intelligence needs improvements in automation scripts and SDK/API accuracy. Modernizing the user interface and enhancing workflow integrations are also needed. Atlan could benefit from enhanced API documentation and a more robust governance framework. Faster support response times and improved data observability would further enhance user experience.

Ease of Deployment and Customer Service: Erwin Data Intelligence supports hybrid, on-premises, and cloud deployments, featuring reliable but sometimes slow customer service. Premium support options are available for timely resolutions. Atlan offers similar deployment options but stands out with a responsive helpdesk, comparable to in-house service levels, enhancing day-to-day operations through rapid assistance.

Pricing and ROI: Erwin Data Intelligence is considered cost-effective, offering comprehensive governance features with a focus on reducing labor costs and increasing process efficiency. Atlan’s pricing, based on user count, is favorable for mid-sized organizations, offering a cost-effective alternative to platforms like Collibra. Both products showcase significant ROI by optimizing data handling efficiency and supporting automation efforts.

To learn more, read our detailed Atlan vs. Quest Data Intelligence Report (Updated: July 2026).

Buyer's Guide

Atlan vs. Quest Data Intelligence

July 2026

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Helped 911,493 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

Ranking in Metadata Management

5th

Average Rating

8.4

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Quest Data Intelligence

Ranking in Data Governance

18th

Ranking in Metadata Management

7th

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

AI Governance (3rd)

Mindshare comparison

As of August 2026, in the Data Governance category, the mindshare of Atlan is 1.8%, down from 2.1% compared to the previous year. The mindshare of Quest Data Intelligence is 2.5%, up from 2.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Governance Mindshare Distribution
Product	Mindshare (%)
Atlan	1.8%
Quest Data Intelligence	2.5%
Other	95.7%

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.

Read full review

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.

Read full review

Quotes from Members

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

Pros

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

"By switching to Atlan, we have increased our productivity and saved a lot of business time through automation."

"Atlan has positively impacted the organization since it helps in discovering already available assets, allowing for reduction of redundant ingestion of external data and reduction of time to market for any project."

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

"The technical support services are good."

"Atlas is quite intuitive."

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

"By switching to Atlan, we have increased our productivity and saved a lot of business time."

More Atlan pros

"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."

"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."

"If I use a traditional ETL tool and build it through an IT port, it would take five days to build very simple data mapping to get it to the deployment phase, whereas using this solution, the IT cost will be cut down to less than a day."

"This tool has taken us from having nothing to being very efficient."

"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."

"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."

"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."

"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."

More Quest Data Intelligence pros

Cons

"The product could be improved by offering scheduled email reports for managed assets."

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

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

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

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

"The challenge is in the lineage, where it requires improvement. Atlas needs to capture areas where organizations use less known applications."

"In my experience, it might be less suited for collaboration across teams."

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

More Atlan cons

"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."

"There is room for improvement in automation, no question."

"There is room for improvement with the data cataloging capability. Right now, there is a list of a lot of sources that they can catalog, or they can create metadata upon, but if they can add more then that would be a good plus for this tool."

"Scalability has room for improvement. It tends to slow down when we have large volumes of data, and it takes more time."

"Improvement is required for the AIMatch feature, which is supposed to help automatically discover relationships in data."

"The data quality assessment requires third-party components and a separate license."

"There may be some opportunities for improvement in terms of the user interface to make it a little bit more intuitive."

"Another area where it can improve is by having BB-Graph-type databases where relationship discovery and relationship identification are much easier."

More Quest 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."

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

"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."

"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."

"The price is too high."

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

"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 Data Catalog is very expensive."

More Quest Data Intelligence pricing and cost advice

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Top Industries

By visitors reading reviews

Manufacturing Company

18%

Financial Services Firm

Energy/Utilities Company

Insurance Company

Financial Services Firm

14%

Government

Construction Company

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	1
Midsize Enterprise	1
Large Enterprise	9

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	16

Questions from the Community

What is your experience regarding pricing and costs for Atlan?

My experience with pricing, setup cost, and licensing is that the licensing cost is a bit flexible but not affordable for smaller organizations. It might be way out of their budget, but it is very ...

See all answers

What needs improvement with Atlan?

Atlan can be improved by enhancing their support process by reducing the resolution time. They have really bad and incomplete documentation, so they should work on the documentation as well, especi...

See all answers

What is your primary use case for Atlan?

My main use case for Atlan is to define a flexible set of metadata, including measuring the quality of said data. Atlan is also a partner of ours, so we use it to integrate with our own tool. It al...

See all answers

What needs improvement with erwin Data Intelligence by Quest?

In my opinion, the analytics part of erwin Data Intelligence is not satisfactory. The name 'Intelligence' is not related specifically to analytics; it is focused on data governance with no advanced...

See all answers

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

My main use case for erwin Data Intelligence is applying it and the DQ Labs in a financial institution.

See all answers

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

The integration of business glossaries has significantly helped improve collaboration in our organization. We define the business glossaries first during meetings with the business, and then we bul...

See all answers

Comparisons

Microsoft Purview Data Governance vs Atlan

Compared 15% of the time

Alation Data Catalog vs Atlan

Compared 13% of the time

Collibra Platform vs Atlan

Compared 12% of the time

Dawiso vs Atlan

Compared 8% of the time

MANTA Flow vs Atlan

Compared 3% of the time

More Atlan Competitors

Collibra Platform vs Quest Data Intelligence

Compared 18% of the time

Alation Data Catalog vs Quest Data Intelligence

Compared 10% of the time

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

Compared 7% of the time

Microsoft Purview Data Governance vs Quest Data Intelligence

Compared 5% of the time

AtScale Adaptive Analytics (A3) vs Quest Data Intelligence

Compared 2% of the time

More Quest Data Intelligence Competitors

Product Reports

Buyer's Guide

Atlan

August 2026

Download Atlan product report

Buyer's Guide

Quest Data Intelligence

August 2026

Download Quest Data Intelligence product report

Also Known As

No data available

erwin DG, erwin Data Governance, erwin Data Catalog

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 is a comprehensive platform for metadata management, data cataloging, and governance. It enables organizations to gain insights, improve traceability, and streamline compliance through its advanced features.

Focusing on data lineage, metadata repositories, and seamless integrations, erwin Data Intelligence provides a unified perspective of enterprise data. Its robust capabilities include Smart Data Connectors for automation, efficient data visualization with mind maps, and adaptable metadata properties. While the platform integrates well into existing systems, areas for improvement include automation, SDK inconsistencies, and the need for better data quality assessments. Use cases highlight its importance in enhancing business data models and regulatory compliance.

What are the key features of erwin Data Intelligence?

Single Source of Truth: Centralizes data for consistent information across the organization.
Smart Data Connectors: Automate connections to data sources, enhancing efficiency.
Data Lineage: Tracks data pathways for better traceability and understanding.
Business Glossaries: Enables clear definitions and shared vocabulary for all users.
Metadata Management: Streamlines metadata organization and retrieval.
Impact Analysis: Assesses implications of data changes rapidly and accurately.

What benefits should users look for in reviews?

Enhanced Efficiency: Automation scripts reduce manual processes and increase productivity.
Improved Data Visualization: Mind maps facilitate an intuitive understanding of complex data.
Customizable Properties: Adapt metadata attributes to fit specific organizational requirements.
Unified View: Offers a comprehensive perspective of data governance practices.

Industries implementing erwin Data Intelligence often focus on mapping data sources and integrating governance with ETL tools. This supports comprehensive data management strategies, enabling business teams to better locate, understand, and utilize data effectively. Its application in metadata management and automated reporting is particularly valuable in sectors requiring stringent regulatory compliance.

Quest Software

Sample Customers

Information Not Available

Oracle, Infosys, GSK, Toyota Motor Sales, HSBC

Buyer's Guide

Atlan vs. Quest Data Intelligence

July 2026

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