Cost Optimization Guide
Log storage cost comparison: Datadog and S3
Not all logs need expensive indexed storage. Matching storage tier to use case is a major cost lever.
Why this problem exists
Teams often keep all data in one tier for convenience.
Retention requirements and incident workflows are mixed into a single storage policy.
Real cost and impact
Indexed platforms provide speed but become costly for full-fidelity long retention.
Archival storage is materially cheaper for logs that are rarely queried.
Solutions (including alternatives)
- Keep recent, high-signal operational logs in Datadog for fast triage.
- Store full raw stream in S3 for compliance and long-horizon analysis.
- Continuously tune what qualifies as high-signal based on alert and incident usage.
How LogTrim solves it
LogTrim supports dual routing so teams can enforce hot-vs-cold retention policy automatically.
This balances operational speed and cost control.
Example scenario
A team reduced indexed retention scope while maintaining full S3 archives for audits.
They kept searchable incident data where it mattered most.
Reduce your costs with LogTrim
Start with high-noise categories, keep high-signal logs in Datadog, and archive full retention in S3.