How to Model the Cost of a Self-Hosted Analytics Stack
Compare managed, self-hosted, and in-house analytics costs with a workload model based on your own event volume and engineering time.
This is a planning framework, not a customer result. Replace every input with costs from your own infrastructure and team.
The cheapest analytics option is not always the plan with the lowest license fee. Compare the total cost of a managed service, a self-hosted product, and an in-house build using the same traffic, retention, reliability, and staffing assumptions.
Use one workload for every option
Record these inputs before requesting quotes:
- monthly events and peak events per second
- average event payload size
- hot and archive retention periods
- number of regions and environments
- required recovery point and recovery time
- destination delivery volume
- expected annual traffic growth
Without a shared workload, vendor and cloud estimates do not describe the same system.
Include the costs outside the database
For each option, estimate:
- Compute, storage, networking, backups, and observability.
- Product or support fees.
- Initial implementation and migration work.
- Ongoing engineering, security, and on-call time.
- Capacity reserved for traffic spikes and recovery.
A simple annual model is:
annual cost = infrastructure + software + implementation + operations + contingency
Use loaded employee cost rather than salary alone. Include time spent on schema changes, failed delivery retries, upgrades, incident response, access reviews, and deletion requests.
Compare the operating models
| Option | Your team owns | Vendor owns |
|---|---|---|
| Managed Hardal | Instrumentation, policy, and destination configuration | Platform operation and product updates |
| Self-hosted Hardal | Cloud account, capacity, and internal access | Product software and implementation support |
| In-house build | Collection, storage, delivery, UI, security, and on-call | Nothing unless contracted separately |
Self-hosting can fit a strict residency policy or an existing platform team. A managed deployment can fit teams that want to keep infrastructure out of their on-call rotation. An in-house build can make sense when the event pipeline itself is a durable product advantage.
Decision checklist
- Can the option run in the required region or cloud account?
- Who owns upgrades, backups, and incident response?
- How does cost change at twice the current event volume?
- Can you export raw events without rebuilding the pipeline?
- Which security and privacy controls still require internal work?
- What is the exit plan if the chosen model changes?
Use the tracking cost calculator for an initial estimate, then compare the assumptions with Hardal pricing and the self-hosted deployment model.
