Collibra
vs Atlan

Industry experts and practitioners who have used both agree: there's simply no comparison to Atlan.

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Collibra vs Atlan: Why 75% of data teams chose Atlan after evaluating both platforms

Six top reasons why data teams choose Atlan over legacy tools in head-to-head trials

Automation first product actions for faster time-to-value
Robust and automated column-level lineage for end-to-end visibility of data estate
Adoption-centric design for viral use and business engagement in the enterprise
Configurable to meet diverse needs (personas, tech stack, use cases etc.) of data teams
Extensible and open platform for driving advanced programmatic metadata use cases
Partner not vendor approach to make customers successful in their critical business initiatives

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Collibra vs Atlan:
Which Drives Better Business Outcomes?

Here's a quick overview of how Collibra and Atlan compare in terms of driving business value

Factor
Enabling self-service analytics across your org	Not the easiest to use, and no easy way to collaborate with data experts	Non-technical users typically start self-serving their data requests within a month of deployment
Encouraging adoption across your org	Non-intuitive UI/UX and poor product experience, leading to poor adoption	Intuitive collaboration-focused UI/UX, any type of user can hit the ground running
Ease of setting up	Setup requires 4 months or more, need implementation support experts	DIY setup, typically in weeks
Time to experience actual value	Long time to value, often taking a year or more, after a cumbersome multi-month deployment cycle. The major roadblock to realizing value is the lack of adoption	First metadata-driven value is in a matter of weeks not months. Easy adoption by diverse stakeholders makes value inevitable
Keeping pace with how you grow as a business	May not handle change well. Legacy platform, a closed solution, incapable of supporting modern paradigms like data mesh, data fabric and data-as-a-product.	Is open to change in your stack and growth. Open-by-design, cloud-first, Kubernetes-based platform with natively built-in microservices. Supports modern frameworks like data mesh, data fabric, data-as-a-product
Bringing visibility into your entire data estate	Focused on the breadth of integrations vs depth of integrations. Better for on-prem integrations, but not good for cloud-native modern tools	Deep integrations with cloud-native modern tools. Cloud-first, cloud-native platform as core DNA. Connects to major on-prem providers and others in roadmap
The overall cost of deployment and maintenance	Prohibitive costs due to high people cost and implementation costs. Relies on manual stewardship to enrich assets, needing a large team. For a large organization, this cost can easily come out to 6x of the cost of the tooling itself. Also requires an SI expert familiar with the platform to set it up successfully. This cost alone can run north of $1M for large organizations.	Setup and maintenance costs are low, as it embraces an automation first and cloud first modern approach in tool setup and maintenance

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Collibra vs Atlan:
Which solution is the most future ready?

Collibra and Atlan are two generationally different products. Collibra is a traditional data governance tool. Atlan is an active metadata platform.

Here are some key differences in how the platforms are being built:

Factor
Forward looking architecture	Static closed platform that operates in silos	Open, scalable, tech-debt-free platform, suited for modern paradigms like data fabric and data mesh
Active governance	Manual stewardship governance model	Programmatic governance through metadata activation
AI/ML capabilities	Very limited AI/ML product capabilities	Atlan AI powering use cases like auto documentation at scale, auto generate SQL using natural language, natural language lineage summaries, AI-copilot etc.

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Why Yape chose Atlan over Collibra

Yape is a fast-growing payment app from Financial Services holding company Credicorp, offering a P2P digital wallet to more than 13 million users across Peru.

Ease of setup
“It was easy to use, your connectors with Databricks and our data ecosystem worked really well”, “We implemented Atlan over a three-week phase with our own data by running 5 use cases with 21 activities in total, which drove a lot of value for us”
Future proof
“We needed a platform for innovation to stay ahead of our competitors… That’s what I really liked about Atlan. You’re constantly innovating with the latest trends, you have Atlan AI, you support Data Mesh natively and enhance it with your new product, Atlan Mesh.”
UX built for adoption
“You have the best UI in the market right now. For me, the most important thing is that we chose a tool that’s not only for tech people, but for everybody so we can democratize access to data”
Faster time to value
“We have an agile mindset, and we move really fast to try new tools and integrate them into our data ecosystem. This was another point where the data culture of Atlan fit really well with us.”

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Collibra vs Atlan:
The long and short of it

Collibra is a traditional data governance tool, while Atlan is a pioneering active metadata platform. Atlan is not just rated over Collibra in terms of product functionality, but also in product vision, innovation roadmap, and market approach. The company focuses on constant innovation and partnering with customers to generate value.