2 Best Open Source Datadog Alternatives

A curated collection of the best open source alternatives to Datadog.

Ege Beşe's profile

Written by Ege Beşe

The best open source alternative to Datadog is grafana. If that doesn't suit you, we've compiled a ranked list of open source Datadog alternatives to help you find a replacement.

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Datadog

Datadog is a cloud-based monitoring and observability platform for tracking infrastructure metrics, logs, and application performance.
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Datadog is a hosted observability platform that collects metrics, logs, and traces from applications and infrastructure, then presents them through dashboards, alerts, and anomaly detection. It covers a broad range of monitoring needs, from server metrics to application performance monitoring, in a single connected product with many built-in integrations.

Teams look for open-source alternatives to Datadog mostly because of cost, since Datadog's pricing is based on hosts, custom metrics, and log volume, and bills can grow quickly as infrastructure scales or logging increases. Others want to keep monitoring data on their own infrastructure, or want to avoid depending on a single vendor for something as central as observability.

Grafana and Prometheus together form the most common open-source substitute. Prometheus collects and stores time-series metrics, while Grafana provides dashboards and visualization on top of that data, and the pair is often extended with tools like Loki for logs to cover more of what Datadog offers as one product. This gives teams control over retention, storage location, and cost, but it means assembling and maintaining several components instead of using one integrated service.

Before switching, map out which Datadog features you rely on beyond basic metrics and dashboards, such as APM tracing or specific integrations, since replicating the full feature set may require additional open-source tools beyond Grafana and Prometheus. Plan for the operational work of running and scaling this stack yourself, including storage retention and high availability for the metrics database. Also budget time for rebuilding dashboards and alerts, since configurations do not transfer automatically between platforms.

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