How Much Does Collibra Cost? Full Cost Breakdown for Enterprise Buyers in 2026

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How does Collibra pricing work? Six fundamental pricing factors to consider

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The cost of a data catalog is more than just a price tag. Only when you have a complete picture of the total cost of ownership (TCO) can you decide whether it brings enough value relative to the expense.

To estimate the TCO accurately, you need to consider the following costs together:

1. Base platform costs
2. Upfront licensing fees
3. Hosting costs
4. Implementation costs
5. People costs
6. Ongoing maintenance and troubleshooting costs

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1. Base subscription (Starting Point: ~$170k/year)

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The base price includes the core catalog and essential platform capabilities. Marketplace (AWS) listings show offerings for Collibra Cloud Platform beginning at ~$170k annually. This is just for access to the platform.

2. Upfront licensing fees

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Licensing fee structures vary depending on the service provider. These usually depend upon several factors, including but not limited to:

• Number of ordinary users
• Number of administrative users
• Number of data connectors used to connect to your data sources throughout your data estate
• Other features that the vendor has deemed “add-ons”

In general, for a tool like Collibra, the base licensing cost will represent around 30-50% of the total licensing cost, with data connector and user fees comprising the remainder.

Licensing costs for Collibra in particular can add up as the company licenses price different features separately. One user notes in a review, for example, that they paid separate licensing fees for Collibra Governance, Lineage, and Data Quality.

Connectors in Collibra also differ in pricing based on the type of connector, which makes it even more challenging to figure out pricing. Moreover, obtaining lineage from a data source with Collibra’s lineage harvester is also known to incur an additional cost.

3. Hosting costs

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There are three basic ways you can consume a data catalog:

• As a Software as a Service (SaaS) offering
• As a cloud-based catalog deployed to a general cloud services provider, such as Amazon Web Services (AWS) or Google Compute Platform (GCP)
• As an on-premise catalog, i.e., hosted in your own data centers

If computing in the cloud or on-premise, a data catalog requires devoted storage and computation. Depending on your hosting service, there may be data egress costs as you transfer between systems. An on-premise installation will also incur additional capital expenses in terms of server racks and other hardware.

For SaaS offerings, hosting costs will generally be baked into the licensing cost. However, there may likely be additional charges for exceeding set capacity amounts (for example, a certain number of GB of data egress or metadata storage).

Collibra runs as a SaaS product that the company deploys for its users. As such, hosting costs are built into the core licensing fees. Other reviewers have said that while Collibra’s cloud support seems solid, their support for on-premises use cases leaves a lot to be desired.

4. Implementation costs

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Many legacy data catalogs are notoriously hard to install. As mentioned earlier, this often requires hiring system integrators (SIs) who specialize in the platform, and those professionals don’t come cheap.

If a catalog takes months to set up or doesn’t integrate properly with your data systems, the lost time and effort quickly become expensive. Moreover, hiring dedicated support can incur an additional cost of £81,500 (USD 109k) per year.

That’s why it’s important to deploy a data catalog that supports an easy, DIY installation.

5. People costs

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The ‘people costs’ that come with implementing a data catalog can be as much as 6X of the base licensing costs with a data catalog like Collibra. This includes:

• Fully integrating the data catalog into an organization’s existing architecture
• Connecting the organization’s numerous complex data sources to the data catalog
• Pulling a team of data stewards together to enrich the metadata (the largest of the three costs)

Some public reviews indicate that Collibra makes this more difficult. One said that “setting up the tool and seeing results takes a significant amount of time and manual effort.”

The lack of available consultants to help with setup also increases the difficulty of adoption.

It doesn’t end here. Once you get the tool in place, you’ll need to train all data users across the organization. The cost of training varies greatly because it depends on how complex the tool is to learn and use and how long it takes for a generic data user to get onboarded and start benefiting from the data catalog.

With some tools that don’t have clear documentation and guides, training can be a continuous process as you’ll keep discovering issues and looking for solutions. This can occupy a significant portion of an employee’s time.

6. Ongoing maintenance and troubleshooting costs

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Every software system runs into issues. A data catalog is no different. Your data engineering team should have a stable, low-defect data catalog that provides clear, easy-to-use tooling to diagnose problems such as system integration or data source connection issues.

If documentation is unclear or support isn’t available when you need it, you could lose valuable uptime. Additionally, if the system is hard to troubleshoot and debug, i.e., it doesn’t emit clear and verbose error messages, there’s little dashboarding to track metrics, or it isn’t clear where/how to access logs, then your engineers may find themselves with a growing backlog of support tickets that it takes days to resolve.

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What is the TCO for Collibra?

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Collibra’s total cost of ownership (TCO) is significantly shaped by its steep learning curve, heavy configuration requirements, and limited business-user adoption.

Because Collibra requires extensive manual modeling, workflow setup, and metadata enrichment, enterprises often face long “wind-up” periods where:

• Engineering time is diverted to configuring Collibra instead of building data products
• The catalog is not yet usable, delaying value realization

A Fortune 500 U.S. utility we worked with reported that manual enrichment and workflow setup slowed their deployment, resulting in months before the platform delivered meaningful value.

Even after go-live, the biggest TCO challenge is adoption. Collibra’s technical UI and governance-first workflows often fail to resonate with business users. When analysts and domain teams don’t engage, engineering teams remain the bottleneck—servicing BI requests manually instead of relying on a shared catalog.

For example, one Fortune 500 consumer packaged goods (CPG) company we worked with switched from Collibra to Atlan specifically because of issues they encountered with end-user adoption.

You can see this sentiment echoed in public reviews – while the platform may be useful for engineers, business teams struggle to engage with the involved user experience.

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How can you get the actual pricing for Collibra?

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Collibra keeps pricing private. To get specifics, you must:

• Contact their sales team for a tailored quote based on your environment and use cases.
• Clarify your requirements as pricing depends heavily on:
  • Which modules you need (Catalog, Governance, Data Quality, Lineage, Privacy, etc.)
  • Number and type of users (admins, stewards, analysts, creators)
  • Deployment method (Collibra Cloud vs. on-prem)
  • Data volume and integration requirements
  • Level of support, customer success, and professional services

Collibra’s TCO tends to grow with scale—more datasets, more users, and more workflows typically require additional services and configuration.

Many organizations compare Collibra with modern active metadata platforms like Atlan, which emphasize faster rollout, lower admin burden, and higher adoption across technical + business teams.

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Real stories, real customers: Why modern enterprises chose Atlan (instead of Collibra) for cataloging and governance

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Is Collibra right for you?

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If you want a data platform focused on technical tools for engineering teams who have time to spend on training, Collibra may be an okay option. If you want a platform that connects business teams to data sources and enables self-service and collaboration, however, it isn’t the best fit.

Atlan offers a data catalog, data governance, and lineage tools, enabling data exploration and understanding for every data producer and data consumer in your organization.

To see for yourself, request a personalized demo today.

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FAQs about Collibra pricing

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1. What influences Collibra’s pricing the most?

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The biggest drivers are:

• Number of users and personas
• Number of governance modules
• Required connectors
• Lineage and DQ add-ons
• Implementation services

2. How does Collibra’s pricing compare to other data catalog solutions?

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Collibra is generally one of the highest-priced governance platforms due to:

• Modular add-ons
• Stewardship-heavy workflows
• Professional services requirements

Modern platforms like Atlan often show lower TCO and faster implementation.

3. Are there any hidden costs associated with Collibra pricing?

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Common hidden costs include:

• Workflow customization
• Lineage ingestion services
• Metadata modeling consulting
• Ongoing admin staff
• Additional connectors not included in base license

4. Does Collibra offer a free trial?

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No. Collibra does not provide a public free trial. Access is restricted to enterprise buyers through sales engagements.

5. How long does Collibra take to implement?

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According to customer reviews on G2, Collibra’s average implementation time is six months, with ROI typically achieved after 25 months.

6. Does Collibra charge extra for data lineage or data quality?

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Yes. Lineage and data quality are separate modules with their own licensing and implementation fees.

7. Does a higher price mean Collibra is a better or more premium solution?

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No. A higher price doesn’t guarantee faster time-to-value, easier adoption, or better outcomes. Collibra’s pricing reflects its legacy governance-first model and complexity—not necessarily superior performance. The best solution is the one your teams can actually deploy, use, and scale.

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