loghq vs Datadog
Datadog is an everything platform: infrastructure metrics, logs, APM, real-user monitoring, and Error Tracking as one module inside it. If you already live in Datadog, its error tracking is right there next to everything else. If errors are most of what you need, that breadth is a lot of platform and cost to carry. loghq is focused error tracking you can self-host for a fraction of the surface area.
loghq and Datadog, side by side
Where Datadog still leads: it correlates errors with infrastructure, logs, traces, and RUM in one place. For full-stack observability across a large fleet, nothing here matches its reach.
Why teams pick loghq
Own your data
Datadog is SaaS only, billed by hosts and usage. loghq self-hosts on your own Postgres, with retention you control.
Just error tracking
If you need errors, not the whole observability platform, loghq is a far smaller thing to run and pay for.
Open source
loghq is open and self-hostable, so there is no per-host meter on where your error data lives.
Credit where it is due
Datadog’s reach is the point: errors sit next to logs, traces, and infra in one pane. loghq is not trying to replace that. It replaces the error-tracking slice for teams that want it focused, open, and self-hosted.
What loghq is
Open-source error and crash tracking you can run on your own Postgres, or use on a hosted tier. Automatic capture, fingerprint grouping, source-mapped traces, releases, and alerts, without the rest of an observability suite.