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Atlan vs Data Hub comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Mar 8, 2026

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 Metadata Management
5th
Average Rating
8.4
Reviews Sentiment
5.8
Number of Reviews
10
Ranking in other categories
Data Governance (13th)
Data Hub
Ranking in Metadata Management
4th
Average Rating
8.2
Reviews Sentiment
4.8
Number of Reviews
22
Ranking in other categories
AI Observability (9th)
 

Mindshare comparison

As of October 2026, in the Metadata Management category, the mindshare of Atlan is 4.5%, down from 4.7% compared to the previous year. The mindshare of Data Hub is 2.7%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Metadata Management Mindshare Distribution
ProductMindshare (%)
Data Hub2.7%
Atlan4.5%
Other92.8%
Metadata Management
 

Featured Reviews

Peter Neumann - PeerSpot reviewer
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.
Akashkhurana Hirana - PeerSpot reviewer
Senior Software Engineer 2 at Porch
Metadata management has streamlined lineage tracking and data discovery for our teams
The best features Data Hub offers include its integration capability with many popular tools like Apache Airflow, Snowflake, dbt, Looker, Apache Kafka, and BigQuery. These tools provide us with data in various places, and we commonly use Apache Airflow for the DAG, while utilizing BigQuery as our database and Apache Kafka for consuming messaging queues. Data Hub easily connects with all these tools and features excellent data discovery and visualization capabilities. We can see data visibility, where it comes from, its upstream and downstream relationships. If we remove a column, we can assess the impact of that change. Furthermore, if there are duplicate datasets being used by different teams that do not communicate regularly, onboarding all data to Data Hub allows us to identify these duplicates easily. Out of all those features, I believe data discovery and impact analysis are the most valuable for my team because when we want to add or drop a column, we can assess the impact analysis to understand the downstream effects. This helps us know who owns a dataset, and we can easily contact the owner. Tracking the data lineage back to the source table is also a key benefit. Data Hub has positively impacted my organization by significantly reducing manual work that was previously needed to identify upstream and downstream data relationships, as well as recognizing duplicate datasets. If a data contract is broken, we now easily get notified of those issues, making the process much easier and more efficient. It is particularly useful for data engineers and platform teams to check for problems directly within Data Hub. Data Hub has saved our team a lot of time. For example, in a large company like Porch, if I want to know whether a specific dataset exists, I can check Data Hub, as it serves as a centralized point for managing the metadata of our data. While it does not contain all data, it does contain the metadata necessary for understanding the dataset's origin. If a dataset does not exist, I can simply see who the owner is and reach out to them, which reduces the dependency on others by providing direct access to information in Data Hub.

Quotes from Members

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

Pros

"By switching to Atlan, we have increased our productivity and saved a lot of business time."
"The best feature of Atlan is its integration with communication platforms like Microsoft Teams and Slack, so business users don't have to go into a data catalog to see metadata about data assets."
"Overall, I rate Atlan a nine out of ten."
"The AI part is integrated for enriching metadata engagement, making it a comprehensive tool."
"Overall, I rate Atlan as a ten out of ten."
"By switching to Atlan, we have increased our productivity and saved a lot of business time through automation."
"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."
"Atlas is quite intuitive."
"We have seen a return on investment from using Data Hub, as it saves our data governance team time by collating metadata and viewing the live data dictionary, and it is very helpful in building data quality for the company, leading to approximately thirty percent improvement in efficiency."
"Data Hub positively impacts my organization and clients by making it easier to search for data, facilitating collaboration, and helping save time."
"We made it a place where all stakeholders in our company could log in and see which data were used for which data marts, which column values meant for which definitions, and how they were measured."
"Data Hub has positively impacted my organization as teams can now be directly dependent on one source of truth for all their data needs."
"Data Hub has positively impacted our organization by reducing the knowledge transition period from three months to one month for new team members, enabling them to refer to the complete lineage without depending heavily on others, which is a substantial improvement."
"Acryl Data helps with processing large amounts of data as it is a very good tool that gives good flexibility to store a huge amount of data and is easier to use."
"Data Hub has impacted my organization positively by helping us build a data governance environment and share the knowledge about the data for the entire company."
"Data Hub has positively impacted my organization by significantly reducing manual work that was previously needed to identify upstream and downstream data relationships, as well as recognizing duplicate datasets."
 

Cons

"One area that could be improved is the capability to find duplicates of datasets."
"The product could be improved by offering scheduled email reports for managed assets."
"Atlan can be improved by integrating agents that can support users in finding assets of interest."
"Certain UI changes could make Atlan more user-friendly."
"Customer support for Atlan is not so proactive."
"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."
"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."
"I think Data Hub can be improved by supporting the open source version better."
"Regarding enhancements for complex projects, I have noticed that sometimes Data Hub does not provide a complete picture of the lineage, particularly in complex data pipelines such as when we fetch data from an API to S3 and subsequently to Snowflake."
"We encountered some issues when we wanted to connect our streaming infrastructure to Data Hub, which was somewhat problematic."
"In terms of ROI, I would say that Atlan is better. The way Data Hub is implemented at the moment, Atlan is much better; it's much, much faster."
"Integrating Data Hub with our existing tools and systems was not very easy, which is why my rating is an eight."
"Regarding what I dislike about Data Hub, I think the UI is minimalistic, and I found myself lost sometimes when looking for a specific dataset."
"I chose seven out of ten because there are better catalogs available in the market that offer more features."
"I believe Data Hub could provide more functionalities in the free version."
 

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."
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Top Industries

By visitors reading reviews
Manufacturing Company
18%
Financial Services Firm
9%
Insurance Company
8%
Energy/Utilities Company
7%
Financial Services Firm
16%
Outsourcing Company
12%
Construction Company
9%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise1
Large Enterprise9
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise7
Large Enterprise15
 

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 ...
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...
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...
What needs improvement with Data Hub?
Data Hub can be improved with easy accessibility. I think integration with other environments is needed to enhance accessibility.
What is your primary use case for Data Hub?
My main use case for Data Hub is for data governance, specifically the use of data lineage and data catalog. I use Data Hub for data governance and data lineage in my day-to-day work by checking th...
What advice do you have for others considering Data Hub?
I do not have any advice to give to others looking into using Data Hub. I found this interview valuable and do not think anything needs to change for the future. My overall review rating for Data H...
 

Also Known As

No data available
Acryl Data
 

Overview

Find out what your peers are saying about Atlan vs. Data Hub and other solutions. Updated: September 2026.
917,403 professionals have used our research since 2012.