Sold by: AtlanÂ
Deployed on AWS
Atlan is an active metadata platform built to address the everyday chaos and collaboration overhead faced by data-driven teams. Key features include: data catalog & discovery, data lineage & governance, data quality & profiling, and data exploration.
4.5
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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Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Atlan Platform | Subscription to Atlan Platform starting at | $100,000.00 |
Vendor refund policy
No refunds offered!
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Delivery details
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.
Resources
Vendor resources
Support
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.
Updated weekly
By Alation
By Collibra
Top
10
In Data Catalogs, Data Governance
Top
10
In Data Catalogs, Data Governance, Master Data Management
Top
10
In Data Catalogs, Data Governance
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Discovery
Powerful search algorithms for discovering data assets across tables, views, BI dashboards, SQL snippets, and pipelines
Data Lineage
Automated lineage construction through parsing SQL query history with intelligent bot-driven tracking
Data Governance
Automatic PII data detection with dynamic access policy creation and ecosystem management capabilities
Data Quality Profiling
Automated generation of data quality profiles with variable type detection, frequency distribution, missing value, and outlier analysis
Multi-Platform Integration
Deep integrations with data platforms including Snowflake, Redshift, Databricks, Looker, and Power BI for comprehensive metadata management
Metadata Management
Centralized metadata aggregation from multiple disparate data sources with unified platform capabilities
Behavioral Analysis
Advanced engine for analyzing data usage patterns, interactions, and metadata insights
AI Governance Framework
Comprehensive system for tracking data lineage, ensuring data quality, transparency, and compliance for AI models
Search and Discovery
Automated platform enabling comprehensive search, description, and understanding of data assets including reports and models
Architectural Extensibility
Open and flexible architecture supporting integration across different data environments and platforms
AI Governance
Provides active metadata-driven governance framework for AI strategies with rules, processes, and responsibilities to mitigate risks and ensure ethical AI practices
Data Catalog Management
Enables comprehensive discovery and understanding of data assets across hybrid and multi-cloud environments with full business context and metadata insights
Automated Data Lineage
Offers end-to-end lineage tracking with complete transparency into data transformation and flow across systems, including summary-level and technical lineage details
Privacy Workflow Automation
Centralizes and automates privacy workflows to address global regulatory requirements and encourage collaborative data protection
Data Quality Management
Replaces manual processes with automated data monitoring and rule management to scale data quality across enterprise environments
Standard contract
No
No
Customer reviews
reviewer2784381
Improved data discovery has reduced redundant ingestion and now supports governed asset management
Reviewed on Dec 05, 2025
Review from a verified AWS customer
What is our primary use case?
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 discovery and management.
What is most valuable?
Atlan offers excellent features including support for many different active metadata, such as lineage, which allows visibility into how an asset has been generated.
Active metadata and lineage features help quickly understand if an asset already exists, who the data steward is for that asset, and provide complete visibility on available fields and other technical aspects regarding the asset.
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.
What needs improvement?
Atlan can be improved by integrating agents that can support users in finding assets of interest.
For how long have I used the solution?
Atlan has been used for one and a half years.
What other advice do I have?
I rate Atlan overall a nine out of ten. I choose nine out of ten because even though Atlan is a very good product, it can be further improved. For others looking for a very complete data catalog tool with many features that can support data discovery, lineage, and more, I suggest choosing Atlan.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Information Services
Transforms Data Collaboration with Ease and Efficiency
Reviewed on Nov 09, 2025
Review provided by G2
What do you like best about the product?
What I appreciate most about Atlan is how it transforms working with data into a truly collaborative and seamless experience. By bringing together people, data, and context in a single platform, it enables teams to genuinely understand and trust their data. I find it incredibly easy to locate what I need, document my work, and maintain organization without the usual confusion. Atlan is clearly designed to make data serve people, rather than forcing people to adapt to data. Its smooth integration with modern tools allows teams to work more efficiently, and it makes the entire data process feel more human, transparent, and enjoyable.
What do you dislike about the product?
One aspect I find challenging about Atlan is that it can sometimes feel overwhelming due to the sheer number of features and configuration options. For newcomers, the learning curve is quite steep before you can fully appreciate its value. There are also times when performance slows down, especially when handling very large datasets or complex integrations. Additionally, I would appreciate more flexibility in some customization options to better accommodate specific team workflows. However, these concerns are relatively minor compared to the overall experience—once you become familiar with the platform, Atlan proves to be both powerful and enjoyable to use.
What problems is the product solving and how is that benefiting you?
Atlan addresses one of the most significant challenges in the data world: the lack of visibility, collaboration, and trust in data. By bringing together scattered data assets, documentation, and context into a single, unified workspace, it becomes much easier to discover, understand, and confidently use data without wasting time searching or doubting its accuracy. Personally, Atlan has made collaboration across teams more efficient, reduced reliance on individual expertise, and enhanced overall data quality. It has also simplified onboarding for new team members and sped up decision-making by ensuring everyone has clear and reliable access to the right data when they need it.
Arnold C.
Magically Boosts Productivity and Workflow
Reviewed on Nov 07, 2025
Review provided by G2
What do you like best about the product?
It significantly enhances productivity, streamlines workflow, and makes implementation across the business remarkably easy, almost like magic!
What do you dislike about the product?
The customer support isn't particularly impressive, but it is still an improvement over what I've experienced with other competitors.
What problems is the product solving and how is that benefiting you?
Integration of the source data made seamless and data privacy/storage are top notch that I can sleep without any issues.
Param S.
Gratitude towards Atlan
Reviewed on Nov 04, 2025
Review provided by G2
What do you like best about the product?
Its user friendly data catalog and it is very supportive and collaborative.
What do you dislike about the product?
Limited customization for UI components.
What problems is the product solving and how is that benefiting you?
Ensuring good quality data.
Peter Neumann
Has struggled to meet business needs but supports technical data exploration and transparency
Reviewed on Oct 31, 2025
Review provided by PeerSpot
What is our primary use case?
I have been using Atlan for two years.
My main use case for Atlan includes data catalog, business glossary, import-export, data lineage, lineage import-export, and lineage generator, as I was the intense tester of Atlan.
In my day-to-day work, I use Atlan to analyze databases to find lineage or try to import business glossaries from Excel from several business sources, importing them into Atlan or trying to visualize the lineage, which is exactly what the customer needed. Importing a business glossary connects business terms with some IT tables and columns and makes it visible. What is unique about my main use case is that I was heavily involved in the import-export formatting of data, trying to automate some import-export, figuring out how the templates work for export-import, how the specific import-export workflows run in Atlan, what failures can happen, the uniqueness of data, and finding matching partners in lineage cases.
What is most valuable?
The best features Atlan offers for me include reading the data, having the interfaces, and reading the data from tables from different sources, performing automated import exports, and connecting sources to IT systems, which I consider the biggest strength of Atlan.
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.
Atlan has positively impacted my organization by helping the business people use it to understand where the data is, what meta information is, and attempt to assume the roles of a data owner and a data steward, which was new for them. They find it much easier to search and navigate the data and better understand the data.
The change has affected my team's productivity and collaboration by reducing the time of finding the right data, navigating, and creating a new report, which helped the business people understand their jobs. When creating a new data governance team, it is a challenge for people to assume these roles, and using Atlan was a significant advantage in helping them identify what the role is and begin to assume it.
What needs improvement?
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.
What do I think about the stability of the solution?
Atlan is stable.
What do I think about the scalability of the solution?
I did not hear anything negative regarding Atlan's scalability. We started with a small group and brought business teams or new members on board, and there were no issues at all. Scalability is perfect.
How are customer service and support?
I can only share positive results about Atlan's customer support. They were keen on helping us, providing answers in a very comfortable time frame, making it quick and easy, and they always tried to offer the best solution even for our very customized requirements.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I have experience with many modeling tools including DataSpot, ARISÂ , and Enterprise Architect, but those are not really data catalog tools. Depending on the purpose, it is important to start from the business side for implementations related to data understanding and data catalog, rather than from the technical side.
Which other solutions did I evaluate?
Before choosing Atlan, there were other options such as Collibra and Atlassian, but I was not involved in the proof of concept and we started working once Atlan was selected.
What other advice do I have?
For the user experience, it is sometimes tedious because when reading the source and finding the data tables, if I then try to find matching partners or visualize some lineages, it can be overwhelming. I need to either shrink the scope of my task, use lesser complexity, or use fewer tables to generate business values. Sometimes it can simply be overwhelming.
My advice for others looking into using Atlan is that they must be clear upfront about the purpose and scenario for which they want to use it. If they want to connect databases, read, surf, and do that, then I would recommend it. However, if they want to start a data governance organization or business understanding, that would be a totally different story because Atlan has strengths in technical connections.
Atlan should be made livable for business people. It should not be solely from developers for developers, as there is a vast range of business users who are happy if they can read Excel sheets but do not have knowledge about XML data formats and other technical considerations. If you want to expand your customer range, Atlan should learn business language and not focus so much on technical language, making it usable for business professionals. I rate this product a five out of five.