Teams leave Datadog for three reasons: cost at scale, alert fatigue, and data lock-in. Here’s an honest, ranked field of alternatives — what each is best at, and which one fits the problem you actually have. Last updated July 2026.
Ranked for the GPU/AI-datacenter on-call use case. This page is published by Plexus — we put ourselves first for that specific problem, and we’re straight about what each other tool does better.
Plexus is the operations frontend for hardware fleets. Connect a device with a three-line SDK — or point Plexus at the Postgres, TimescaleDB, MySQL, or ClickHouse you already run (no migration, no ingest bill for data read in place). Dashboards generate themselves from the first data that lands; threshold, event, and offline monitors watch every connection with per-monitor email/Slack/webhook routing; every alert keeps a full, auditable timeline with a captured verdict; and a ⌘K terminal lets you query the fleet in plain language. Usage-priced — $0.10/M metric rows, first $5/mo covered — with no per-host seats.
Plexus vs Datadog →The default open-source observability stack: Prometheus/Thanos for metrics and storage, Grafana for dashboards and alerting. You own the data and pay no per-host SaaS tax — but you also build, wire, and maintain everything yourself. If your metrics land in a store Plexus connects to (Postgres, TimescaleDB, MySQL, ClickHouse), the two can read the same data side by side.
Plexus vs Grafana →An open-source, OTel-native APM that bundles traces, logs, and metrics with a single backend (ClickHouse under the hood). A strong full-platform Datadog alternative if you want broad coverage and self-host or managed cloud. It is a platform to adopt — telemetry moves into it — rather than a frontend on your existing store.
Polished uptime monitoring, incident management, and log management with a generous free tier and approachable pricing. Great for web/services teams; less focused on the GPU/data-center hardware layer.
Uses eBPF to capture telemetry with little instrumentation and keeps data in your own cluster, pitched hard on cost vs Datadog. Strong for Kubernetes observability; built for web and cluster workloads rather than device fleets.
A heavyweight log-analytics and SIEM platform. Powerful and broad, but priced by volume — often the reason teams move off it for infrastructure monitoring. Strong for security/log analytics; heavy and costly if all you need is to cut infra alert noise.
Plexus vs Splunk →If the pain is storage cost, a ClickHouse-backed store (OpenObserve, or your own) is dramatically cheaper than Datadog ingest. But a store is not an operating surface — you still need the frontend on top: dashboards, monitors, alert history. That layer is what Plexus is, and it reads ClickHouse in place.
Plexus vs ClickHouse →Three reasons dominate: cost at scale (per-host and ingest pricing climbs fast on a large GPU fleet), alert fatigue (more, tidier alerts still land on a human), and data lock-in (Datadog's model is to ingest your telemetry into Datadog). GPU/AI data centers feel all three acutely.
For teams operating hardware fleets, Plexus is purpose-built: it connects to the ClickHouse or Postgres your telemetry already lands in (no migration), generates dashboards from the data itself, and puts threshold/event/offline monitors with an auditable alert history on every connection — usage-priced, with no per-host seats. For broad APM coverage, SigNoz is the strongest open-source full-platform option.
It depends. Plexus connects to Postgres, TimescaleDB, MySQL, or ClickHouse in place, and the Grafana/Prometheus stack reads the stores you point it at. SaaS platforms (Datadog, and to a degree SigNoz Cloud, Better Stack) ingest your telemetry into their backend. If avoiding migration matters, prefer the tools that read your existing store.
Yes, when your metrics land in a store both can read — Postgres, TimescaleDB, MySQL, or ClickHouse. Keep every Grafana dashboard you've built, and add Plexus for the parts you'd otherwise assemble: auto-generated fleet views, monitors with per-monitor routing and offline detection, and a per-alert audit trail.