Collibra Pricing: Will It Deliver a Return on Investment?

Updated February 28th, 2024

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Collibra is a data intelligence platform that includes a data catalog, data governance tools, and other features. While these are valuable toolssure, Collibra’s price point can be prohibitive.

Pricing a data catalog requires some consideration. The costs of a tool suite can vary significantly depending on the business needs, which is why you’ll rarely find a straightforward pricing sheet. Additionally, as with any major software purchase, the final price is more than just the total of licenses.

So how do you gauge Collibra pricing? Let’s break it down step-by-step.

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Table of contents #

  1. Collibra pricing overview
  2. Collibra pricing: 5 data catalog setup costs to consider
  3. Collibra pricing: Total cost of ownership
  4. Is Collibra right for you?
  5. Related reads

Collibra pricing overview #

How much does Collibra cost per year? #


Although data catalog pricing can be challenging to find, in Collibra’s case, some baseline information is available from the AWS marketplace. A subscription for Collibra’s intelligence platform is listed at $170,000 annually.

Collibra pricing: Examples of hidden costs #


If you consider other factors, such as people costs or implementation costs, the total operating costs will be higher. Here’s how:

  • People costs: Most of the costs involves in implementing a data catalog come in the form of importing data from a variety of complex sources, as well as enriching metadata. For a large organization with a diverse data estate, this cost can easily come out to 6x of the cost of the tooling itself.
  • Implementation costs: Some users have reported that it can be challenging to get Collibra up and running since there is a shortage of SI (systems integration) partners familiar with the extensive tool suite. Unfortunately, Collibra requires an SI expert familiar with the platform to set it up successfully. This cost can run north of $1M for large organizations.

There are several such factors to consider when evaluating the total cost of implementing a data catalog like Collibra. Let’s explore the most significant factors in the next section.

Collibra pricing: 5 data catalog setup costs to consider #

The cost of a data catalog is more than just a price tag. Data catalogs are systems that interface with an organization’s entire data system.

To understand the cost of a data catalog, you need to consider the following costs together:

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

Only when you have this complete picture of the total cost of ownership can you decide whether it brings enough value relative to the expense.

Let’s get into the specifics.

1. Upfront licensing costs #


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.

2. Hosting costs #


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.

3. Implementation costs #


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

4. People costs #


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.

5. Ongoing maintenance and troubleshooting costs #


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.

Collibra pricing: Total cost of ownership #

So how does Collibra stack up when compared to these TCO considerations?

Collibra’s steep learning curve and poor business-side integration add to the overall cost. A general lack of automation and complex integration requirements also add to the delay in realizing value from your investment.

Every day spent in a wind-up period is engineering time not spent on development. You also lose value because the system isn’t up and running. One Fortune 500 company that we worked with, an American utility and power company, said that the manual effort required for metadata enrichment led to challenges in getting Collibra up and running.

When you finally have the catalog up and running, if business teams can’t leverage it for decision-making, was it even worth the trouble of setting it up? Engineering teams are left serving BI requests rather than leveraging the catalog to find new value in the data.

Looking at the total costs, Collibra may be a good option if business insight needs are low. However, the steep learning curve and lack of experts mean that you will still find yourself waiting for the value to come.

Additionally, Collibra’s tilt towards technical users puts it behind the curve in terms of what modern data catalogs offer. That doesn’t just raise the total cost of ownership; it runs the risk that business teams won’t adopt it at all.

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. There are consistent comments that highlight this sentiment – while the platform may be useful for engineers, business teams struggle to engage with the involved user experience.

Is Collibra right for you? #

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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