Sold by: Atlan
Deployed on AWS
Atlan is the context layer for AI, the infrastructure that makes enterprise AI accurate, trustworthy, and scalable. Trusted by Mastercard, Workday, General Motors, and hundreds of global enterprises, Atlan connects your entire data estate and enriches it with the certified definitions, lineage, ownership, and access policies every AI agent needs. Native integrations with Amazon Redshift, S3, Glue, Athena, Lake Formation, and SageMaker Unified Studio mean your AWS stack is context-ready from day one. Recognized as a Leader in the Gartner Magic Quadrant for Data & Analytics Governance 2026 and Customer Favorite in the Forrester Wave for Data Governance Q3 2025.
4.5
Overview
Atlan is the context layer for AI: the infrastructure that stores, manages, and delivers the business understanding every agent needs to produce accurate, trustworthy outcomes at enterprise scale. That means certified definitions, data lineage, ownership, quality scores, and access policies, available to every agent in your stack, at runtime, through open standards. Without it, agents work with an incomplete picture of your business. With it, they're grounded in what your organization has already built, approved, and certified. Context Agents mine your entire AWS data estate automatically, from S3 and Glue through Redshift and Athena into SageMaker and BI, generating business context that used to take 9-12 months to document manually. 89% of AI-generated context is rated equal to or better than what a human analyst would write, and what took a year now takes two weeks. Context Engineering Studio then runs the full Context Development Lifecycle, Build, Test, Review, Approve, Deploy, Learn, where AI bootstraps context and simulates tests while domain experts resolve ambiguity, add tacit knowledge, and approve before anything ships. Every interaction feeds a compounding learning loop: memory, feedback, and traces make the context layer smarter with every agent query. Atlan's MCP Servers deliver context from a single layer to every agent harness through one open protocol, Amazon Quick Suite, SageMaker Unified Studio, Claude, Copilot, Cursor, Gemini, and any MCP-compatible tool, so every agent operates on the same certified understanding of your business. Native integrations span Amazon Redshift, Amazon S3, AWS Glue, Amazon Athena, AWS Lake Formation, and SageMaker Unified Studio, plus Snowflake, Databricks, dbt, Airflow, and leading BI platforms. Recognized as a Leader in the Gartner Magic Quadrant for Data & Analytics Governance 2026 and Customer Favorite in the Forrester Wave for Data Governance Q3 2025.
Highlights
- Context Mining automatically ingests from your entire AWS data estate, Redshift, S3, Glue, Athena, Lake Formation, and SageMaker. Context Agents then generate business context in two weeks. 89% of AI-generated context rated equal to or better than human-written.
- Context Engineering Studio runs the full Context Development Lifecycle, Build, Test, Review, Approve, Deploy, Learn, where AI bootstraps and simulates while domain experts resolve ambiguity and approve. A compounding learning loop improves context with every agent interaction.
- MCP Servers deliver unified context to every AI agent on AWS, Amazon Quick Suite, SageMaker Unified Studio, Claude, Copilot, and more, through one open protocol.
Details
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Trust Center
Access real-time vendor security and compliance information through their Trust Center powered by Drata or Vanta. Review certifications and security standards before purchase.
Buyer guide
Gain valuable insights from real users who purchased this product, powered by PeerSpot.
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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!
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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/signin
- 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 Atlan
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
Automated Data Discovery and Context Generation
Automatically ingests from AWS data estate including Redshift, S3, Glue, Athena, Lake Formation, and SageMaker to generate business context with certified definitions, lineage, ownership, and quality scores in two weeks.
Context Development Lifecycle Management
Provides Build, Test, Review, Approve, Deploy, and Learn stages where AI bootstraps context and simulates tests while domain experts resolve ambiguity and approve before deployment.
Multi-Agent Context Delivery Protocol
Delivers unified context through MCP Servers to multiple AI agents including Amazon Quick Suite, SageMaker Unified Studio, Claude, Copilot, Cursor, and Gemini via a single open protocol.
Native AWS Data Platform Integrations
Natively integrates with Amazon Redshift, S3, Glue, Athena, Lake Formation, and SageMaker Unified Studio, plus Snowflake, Databricks, dbt, Airflow, and leading BI platforms.
Compounding Learning Loop
Continuously improves context quality through memory, feedback, and traces from every agent interaction, enabling the context layer to become smarter with each query.
Metadata Centralization
Centralizes metadata from disparate sources into a unified platform for discovering, describing, governing, and managing data assets including data, BI reports, and AI models.
Behavioral Analysis Engine
Incorporates a Behavioral Analysis Engine to provide advanced analytics and insights across data assets.
Data Lineage and Tracking
Enables documentation of insights and tracking of data lineage across teams for transparency and compliance purposes.
Self-Service Analytics
Supports self-service analytics capabilities allowing users to independently discover and analyze data assets.
AI Governance Framework
Provides an AI governance framework that ensures data quality, transparency, and compliance for AI initiatives.
AI Governance Framework
Active metadata-based governance with rules, processes and responsibilities to ensure ethical AI practices, mitigate risk, adhere to legal requirements, and protect privacy
Automated Data Lineage
End-to-end lineage tracking providing transparency into data transformation and flow across systems, including both summary-level business lineage and detailed technical lineage
Unified Data Catalog
Multi-cloud and hybrid environment data discovery with business context including data origin, ownership, usage patterns, and access to reports, AI models and data products
Data Quality Automation
Automated monitoring and rule management system for enterprise-wide data quality management replacing manual processes
Privacy and Compliance Workflow
Centralized automation of privacy workflows to operationalize privacy requirements and address global regulatory compliance
Standard contract
No
No
Customer reviews
Manufacturing
Great Lineage and Data Cataloging with Easy Integrations but slow
Reviewed on May 27, 2026
Review provided by G2
What do you like best about the product?
Great lineage and data cataloging functionality. Easy integrations, competitive pricing with good support.
What do you dislike about the product?
The platform can feel sluggish at times. The UI is bland. The initial AI features were incomplete.
What problems is the product solving and how is that benefiting you?
We had a lack of data knowledge across the company. None of our data was AI ready. Atlan is helping us solve both of those problems.
Retail
Great Service and Product—Easy, Intuitive, and Accessible
Reviewed on May 18, 2026
Review provided by G2
What do you like best about the product?
Great service, great product, easy to use
What do you dislike about the product?
Nothing jumps out to me overall very intuitive and accessible
What problems is the product solving and how is that benefiting you?
UNderstanding lineage and how data is flowing and how calculations are performed
Manufacturing
Outstanding Support and Effortless User Adoption
Reviewed on May 14, 2026
Review provided by G2
What do you like best about the product?
The product support and the ease of adoption for users.
What do you dislike about the product?
The sales process could be a bit smoother, but overall no issues
What problems is the product solving and how is that benefiting you?
The Data Product Marketplace is critical to our Data & AI Strategy, a one stop shop to search, discover, learn, contribute and request access
Akash A.
Intuitive, User-Friendly Data Catalog That Makes Finding Datasets Easy
Reviewed on May 06, 2026
Review provided by G2
What do you like best about the product?
What I like most about Atlan is how intuitive and userfriendly it feels. I didn’t have to spend much time learning the tool the interface is clean, and locating the datasets I need is very straightforward.
What do you dislike about the product?
One thing I don’t like about Atlan is that it can feel a bit overwhelming at first, especially if you’re new to data governance or catalog tools. It offers a lot of features, and it takes some time to get familiar with everything and understand how to use those features effectively.
What problems is the product solving and how is that benefiting you?
The main problem Atlan solves for me is data discovery and trust. Before using it, it was often hard to find the right dataset, understand what it actually meant, and feel confident that it was reliable. A lot of time used to be spent asking different teams for context or manually verifying data sources.
Computer Software
Agile, Fast-Moving Startup Vibes—But Needs Stronger Testing
Reviewed on May 05, 2026
Review provided by G2
What do you like best about the product?
It have a good startup vibes with a break fat and move fast approach. The organisation is very agile and adaptive to the industry trends.
What do you dislike about the product?
The are moving so fat that you don't get time to settle up. Testing is very poor.
What problems is the product solving and how is that benefiting you?
They are cataloging metadata of the difference data sources that a customer have. But recently they have shifted there focus from data cataloging to AI based remediation and RCA as they already have a huge amount of client's data sources metadata which can assist in a RCA of any issue