Datadog set the standard for hosted observability, but the hosted model is exactly what a growing number of teams want to move away from. If you are searching for a Datadog alternative, the requirement underneath the search is usually one of two things: stop paying a bill that scales with your data forever, or stop shipping sensitive telemetry to a third-party cloud. A self-hosted, bring-your-own-cloud observability platform addresses both. Here is what that looks like and what to evaluate.
What people are really looking for in a Datadog alternative
- Predictable cost. A model that does not multiply the invoice every time traffic grows or an engineer adds a custom metric.
- Data control. Telemetry that stays in their own cloud for security, compliance, and data-sovereignty reasons.
- No egress tax. An end to paying cloud transfer fees to ship logs and traces out to a SaaS vendor.
- Full fidelity. The ability to keep everything, not sample it away to control spend.
Why BYOC changes the math
In a hosted model, your data lives in the vendor’s cloud and you rent access to it. In a bring-your-own-cloud model, the platform runs in your environment and the data stays put. That single architectural change removes two costs at once: the recurring egress fees to move telemetry out (see observability data egress costs), and the risk and compliance overhead of a third-party copy of your logs (see telemetry security and compliance risk).
Sasquatch Labs runs entirely in your cloud and reduces observability and SIEM cost with lossless compression. You keep every log, metric, and trace, compressed by an order of magnitude or more, and you query it in place with the Snowman engine, which speaks LogQL, SPL, TraceQL, and PromQL. Nothing egresses, nothing is dropped, and there is no separate re-ingestion bill to search your own data.
Self-hosted does not have to mean self-suffering
The old objection to self-hosted observability was operational burden: running your own Elasticsearch cluster is a job. A modern BYOC platform is different. It deploys into your cloud accounts and stores data in your object storage, but you are running purpose-built software, not hand-assembling a stack. You get the control and cost profile of self-hosting without rebuilding a log platform from parts. If you have felt the operational weight of a DIY stack, see why the ELK stack gets expensive and hard to scale.
How to evaluate a Datadog alternative
- Where does the data live? Your cloud or theirs. This drives cost, security, and compliance.
- Does it bill on volume? If cost scales with ingestion, growth is punished. Compression-based pricing rewards keeping data.
- Can you keep everything? Or does cost control require sampling. See sampling vs. lossless.
- Do your query languages carry over? Native LogQL, SPL, TraceQL, and PromQL mean minimal relearning.
A Datadog alternative worth switching to should lower your cost and give you back control of your telemetry, not trade one for the other. See how BYOC observability works at sasquatchlabs.io.