
Overview
Built by a data team for data teams, Atlan is the active metadata platform. With deep integrations with popular tools like Snowflake, Redshift, Databricks, Looker, Power BI and more, Atlan creates a single source of truth by acting as a collaborative workspace for data teams and bringing context back into the tools where data teams live.
Atlan was named a Leader in Forrester Wave - Enterprise Data Catalogs for DataOps and they power data teams in WeWork, Ralph Lauren, Plaid and Postman. Data teams using Atlan have become 6X more agile, improving time-to-insight by up to 60X. Atlan is backed by top investors like Insight, Sequoia & Waterbridge and amazing angels such as the founding teams of Snowflake, Looker, Stitch.
Key features include: data catalog & discovery, data lineage & governance, data quality & profiling, and data exploration.
For startup offers, volume discounts or other custom pricing, or EULA , private contract, please contact marketplace@atlan.comÂ
Highlights
- Make all your data assets from tables, views, BI dashboards, SQL snippets, pipelines, business metrics instantly discoverable. Atlans powerful search algorithms combined with easy browsing experience, make finding the right asset, a breeze.
- Atlan takes the pain away from governing and managing your data ecosystem! Atlan bots parse through SQL query history to auto construct data lineage and auto-detect PII data, allowing you to create dynamic access policies & best in class governance.
- Atlan auto-generates data quality profiles which make detecting bad data, dead easy. From automatic variable type detection & frequency distribution to missing values and outlier detection, we've got you covered.
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Pricing
Dimension | Description | Cost/12 months |
---|---|---|
Atlan Platform | Subscription to Atlan Platform starting at | $100,000.00 |
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No refunds offered!
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Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Vendor support
- Customers can raise support case via ask@atlan.com or via portal https://atlan.zendesk.com/auth/v2/login/signinÂ
- https://ask.atlan.com would be doc site ( same as docs.atlan.com )
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

Standard contract
Customer reviews
Powerful platform for data engineers, but lacking intuitiveness for business users
- Compatibility with open source frameworks like Apache Spark, Airflow
- Great technical catalog for data engineers
- Lineage packages and libraries
- UI / UX was perceived to be too technical
- Great technical catalog but doesn't cover business governance requirements like CDEs
- DataOps Monitoring
- Data Contracts Enforcement
Atlan for modern data management
Setting up the platform was swift, with a few hours of onboarding calls spread over a week. We could quickly run scans on our Snowflake instance and set up integrations with other platforms like dbt. Later, when support for Sigma Computing was introduced, we could integrate the same on our own. Features such as web search of metadata and detailed column-level lineage for root cause and impact analysis were an instant hit with our data power users.
The Atlan customer success team was meticulous in providing us with the necessary support to improve the adoption and engagement on the platform. They consistently strive to understand our specific use cases, deliverables, and business outcomes to provide optimal support. We appreciate how the Atlan team has supported us so far with active metadata management and helping improve the governance of our data and machine learning products.
Using Atlan for Data tagging/Classification
Integration with communication platforms streamlines data access
What is our primary use case?
We are a consulting company, and we propose Atlan as one of the tools in the market. We inform clients that if they are considering a data catalog, they can also consider Atlan . We evaluate it for them, determining whether it would make sense for their organization.
What is most valuable?
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. This integration feature is the coolest thing about Atlan. The ML capabilities that suggest data classifications and provide data descriptions are also impressive.
What needs improvement?
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. Its performance is not optimal when dealing with larger datasets, particularly legacy data assets, as the performance declines when scanning datasets running in terabytes.
For how long have I used the solution?
I have done a couple of POCs using Atlan while working for a company. We were evaluating a few data catalogs, and we included Atlan as one of the prospects.
What do I think about the stability of the solution?
During our POC, the recently launched ML classification system was a hit-and-miss. However, the support team acknowledged it and since then, the feedback from various users indicates that the issues have been resolved, and it's now working well.
What do I think about the scalability of the solution?
Atlan integrates well with smaller datasets, making it suitable for agile companies. However, it struggles with performance when dealing with larger datasets, particularly those running in terabytes.
How are customer service and support?
During the POC, we had a dedicated account executive, and we received good support from them. They helped us navigate our challenges and brought in technical resources whenever required. There were instances when responses took longer than expected, but this could be attributed to us not being a full-time paid customer at that time.
How would you rate customer service and support?
Positive
How was the initial setup?
If implementing the cloud instance, the setup is straightforward and simpler than other tools I have experienced. However, placing it on-premises requires support from data engineering or technical associates.
What's my experience with pricing, setup cost, and licensing?
In comparison to established players like Collibra and Informatica, Atlan is cheaper. However, compared to the next generation of data catalogs like Castor, Atlan is pricier. For mid-sized organizations, Atlan provides a good pricing fit.
Which other solutions did I evaluate?
We evaluated Atlan alongside other data catalogs when working for a company.
What other advice do I have?
Atlan is an eight out of ten, primarily due to its need for improved governance features. If these features are enhanced, it is a ten on ten tool.Â
Atlan has unique ML/AI capabilities that aid engineering teams in documenting without having to start from scratch.Â
Additionally, its integration with communication platforms helps users understand context without accessing the data catalog directly.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Enhanced data management with intuitive data lineage and metadata visualization
What is our primary use case?
One of the primary use cases of Atlan is as an enterprise data catalog. It takes metadata from multiple types of source systems, such as Tableau and Google BigQuery . The platform helps surface everything into a unified data dictionary and data catalog.
How has it helped my organization?
From a business user's perspective, Atlan has reduced the need to bother subject matter experts by surfacing all data and context. It has significantly reduced instances of business users contacting technical SMEs with questions about data content, providing time savings from a human hours perspective.
What is most valuable?
As a senior analytics engineer, Atlan's ability to show end-to-end data lineage is the most important feature for me. It graphically displays the entire data flow, allowing me to understand the flow from source systems to Tableau , including the ability to see SQL scripts behind it and usage metrics. Its capability to automatically pull data descriptions and assign ownership are also noteworthy.
What needs improvement?
Certain UI changes could make Atlan more user-friendly. While they have an Excel add-in for interaction with Atlan, it's in its early stages and could be improved. Additionally, data observability capabilities could be enhanced to provide more alerts on stale or outdated data via communication tools like Microsoft Teams , Slack , or email.
For how long have I used the solution?
I have been using Atlan for almost a year now.
What do I think about the stability of the solution?
Generally, I find Atlan stable. There have been instances where new features temporarily degraded performance. They were quickly optimized by Atlan's engineering team.
What do I think about the scalability of the solution?
There have been no notable scalability issues with Atlan. Its cloud-native backend infrastructure is designed to scale and may require human intervention occasionally, but it handles scalability well.
How are customer service and support?
The customer service and support are pretty good. Any issues are addressed promptly by Atlan's team.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We looked at Google Cloud Platform's Dataplex. It wasn't fit for purpose because we needed an active metadata platform that could provide comprehensive data discovery and data dictionaries.
How was the initial setup?
The initial setup of Atlan was conducted as a minimum viable product, starting with basic capabilities and building up. From the user's perspective, it involved training a small community of super users to promote adoption.
What about the implementation team?
The implementation of Atlan required less than five people from different teams, mainly technical personnel.
What was our ROI?
It's difficult to quantify ROI at the moment due to our immature use of Atlan, however, it has reduced interruptions for technical queries significantly.
What's my experience with pricing, setup cost, and licensing?
The pricing model for Atlan is reasonable compared to other cloud-based platforms. There are different license levels, and we receive a discount on the unit price, making it very competitive.
Which other solutions did I evaluate?
We evaluated Google Cloud Platform's Dataplex, among other tools, yet chose Atlan for its comprehensive capabilities in data lineage and metadata management.
What other advice do I have?
I would recommend dedicated resources from the beginning, including a product manager, as it facilitates better planning and adoption of the solution.Â
Overall, I rate Atlan a nine out of ten. They continue to innovate and listen to customer feedback.