At a glance — how these 5 alternatives compare
Our read on each project's adoption, maintenance activity and commercial-use risk, derived from GitHub signals and SPDX license terms rather than star count alone. Sorted by stars. How we score.
| Project | Adoption | Maintenance | Commercial use |
|---|---|---|---|
| ★ 79,331 · Go | Flagship | Active | High risk Distributing a derived work obliges releasing its source |
| ★ 74,554 · TypeScript | Flagship | Active | High risk Even a hosted/modified deployment can trigger source release |
| ★ 27,403 · TypeScript | Mainstream | Active | Unknown risk No clear SPDX id — treat as all-rights-reserved until verified |
| ★ 19,387 · TypeScript | Mainstream | Active | High risk Even a hosted/modified deployment can trigger source release |
| ★ 9,612 · TypeScript | Mainstream | Active | Low risk Embed in a proprietary product with no copyleft obligation |
The alternatives
netdata
The fastest path to AI-powered full stack observability, even for lean teams.
netdata/netdata Updated 2026-06-21 grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
grafana/grafana Updated 2026-06-20 signoz
SigNoz is an open-source observability platform native to OpenTelemetry with logs, traces and metrics in a single application. An open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool
SigNoz/signoz Updated 2026-06-21 openobserve
Open source observability platform for logs, metrics, traces, frontend monitoring, pipelines and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.
openobserve/openobserve Updated 2026-06-21 hyperdx
Resolve production issues, fast. An open source observability platform unifying session replays, logs, metrics, traces and errors powered by ClickHouse and OpenTelemetry.
hyperdxio/hyperdx Updated 2026-06-20 Editor's take
Yusuke Morinaga · last revisited
A hands-on read of each Datadog alternative — written after running four of them.
I have been the on-call engineer for systems instrumented with each of the five projects above (Netdata for an edge fleet, the Grafana stack for two different SaaS backends, SigNoz on a Kubernetes platform, HyperDX on a Node.js product). The list reads like five interchangeable swap-outs for Datadog. They are not. Each one solves a different shape of the observability problem, and the cost of picking wrong is months of re-instrumentation. Here is what I would tell a peer asking which to start with, project by project.
Netdata — 78k stars, but the star count flatters it
Netdata has more stars than the rest combined, which is genuinely misleading for this list. The bulk of those stars accumulated when Netdata was a single-node, agent-based dashboard for ops people who wanted “top, but a web page” on a server they SSH into. The modern Netdata Cloud product is a different shape — it is a managed correlation layer over the agents — and the OSS agent alone is not really competing with Datadog. If you have a fleet of bare-metal or VM workloads and want per-host vitals with zero config, Netdata wins easily. If you want APM traces correlated with logs across a service mesh, Netdata is not the project to reach for.
The Grafana stack (Grafana + Prometheus + Loki + Tempo) — the honest Datadog replacement
The closest you get to “self-hosted Datadog” is not one of the projects above — it is Grafana plus three sibling projects from the same organisation: Prometheus (or Mimir) for metrics, Loki for logs, Tempo for traces. Grafana itself is the UI layer, which is why it sits in this list. The trade-off is real: you are operating four services, four storage backends, and four sets of YAML, and the correlation Datadog gives you for free (“jump from this slow trace to the logs of that pod”) requires deliberate exemplar configuration in OpenTelemetry. Budget two engineer-weeks of glue work before you get parity. The upside is that each piece is independently swappable — if Loki ingestion costs spiral, you swap Loki for VictoriaLogs without touching Grafana dashboards.
A separate note: Grafana relicensed to AGPL-3.0 starting with the v8.0 release in 2021 (Loki, Tempo, and Mimir followed). The “I am hosting an internal Grafana for my company” case is fine — AGPL only triggers on the network-interaction clause when you modify and then expose the modified version to third parties. If you embed Grafana panels into a SaaS that customers pay for, talk to your lawyer about the iframe vs API boundary before you ship.
SigNoz — the all-in-one bet on OpenTelemetry
SigNoz is the easiest single-product Datadog replacement to demo. One docker-compose, OpenTelemetry collector on the apps, traces/metrics/logs in one UI within an afternoon. The hard part shows up in month three: the ClickHouse backend is fast but has its own operational character (merging, parts, retention TTLs), and the OSS SigNoz alerting is less expressive than Datadog monitors. If your team already runs ClickHouse for analytics, SigNoz is the highest-leverage pick on this list — you reuse one operational competency. If you do not, factor in the ClickHouse learning curve before you commit.
OpenObserve — the storage-conscious choice
OpenObserve’s pitch is “Datadog functionality on object storage” — logs and traces land in S3 (or compatible) rather than block storage. For workloads where log volume is the cost driver (think: noisy Kubernetes clusters), this is a structurally cheaper architecture. The AGPL caveat from Grafana applies here too. The UI is less polished than SigNoz and the APM story is younger, but the storage math wins for high-ingest, lower-QPS log workloads.
HyperDX — the front-end-aware one
HyperDX is the only project in this list that takes session replay seriously as a first-class observability signal. If your team’s “incident” shape is “user reported a broken page”, and you want the backend trace and the recorded browser session in one timeline, HyperDX is the only match here. It is also the youngest project (9.5k stars), so accept that some enterprise features (RBAC granularity, SSO, retention policies) are still maturing. MIT licensed, which makes it the most embedding-friendly of the list.
How I would actually choose
Default for new infra: Grafana stack, biting the operational cost. Default for a single-team SaaS that wants one box: SigNoz. Default for high log volume: OpenObserve. Default for product teams who care about user-side errors: HyperDX. Default for “I just want to see what each box is doing”: Netdata. There is no single answer because Datadog itself is solving five different problems for five different personas — the OSS landscape has unbundled them.
Comparison notes
Grafana + Prometheus covers metrics and dashboards at Datadog scale with self-hosting. OpenTelemetry + Jaeger or Tempo handles distributed tracing. Loki provides log aggregation in the Grafana stack. VictoriaMetrics is a more efficient Prometheus replacement for high-cardinality workloads. The main gaps vs. Datadog: OSS stacks require integrating multiple tools with your own storage backends, whereas Datadog handles retention, scaling, and querying. Datadog's APM automatic instrumentation and cross-service flame graphs require more manual OpenTelemetry configuration to match. Datadog's security monitoring, CSPM, and log anomaly detection have no direct OSS equivalents at comparable maturity.
Migration tips
- Instrument your applications with OpenTelemetry (OTLP) exporters — OpenTelemetry is the vendor-neutral standard that routes to any OSS backend
- Export existing Datadog dashboards as JSON and recreate them in Grafana — many community dashboard templates exist for common stacks
- Migrate Datadog monitors (alerts) to Prometheus alerting rules or Grafana alerts — alert logic translates but syntax differs
- Set up log pipeline (Fluentd/Fluent Bit or Vector) to route logs to your OSS storage before disabling Datadog agents
- Run OSS and Datadog in parallel for at least 2 sprints to validate alert parity before cutting over on-call responsibilities
Which alternative should you pick?
We don't believe in a single "best" answer here — the right project depends on your license constraints, team size, and tolerance for early-stage tooling. The 5 projects above each have a distinct profile. Use this decision tree:
- You want the most active community and the lowest risk of abandonment → netdata. 79,331★ — the largest user base in this list, which usually means more StackOverflow answers, more plugins, and more deployment runbooks online.
- You ship commercial software and need to ship modified code without releasing source → hyperdx. MIT licensed — modify and embed without copyleft obligations.
- You need a project that has shipped a release in the last few weeks → openobserve. Last commit 2026-06-21 — the freshest activity in this list.
License & commercial-use notes
For an open-source replacement the license often matters more than any single feature — it decides whether you can modify the project, embed it in a product, or offer it as a hosted service. Here is how the 5 projects on this page break down:
- Permissive (hyperdx) — MIT / Apache / BSD / ISC — modify and embed inside a commercial product with no copyleft obligation. The safest bucket for shipping in a proprietary codebase.
- Strong copyleft (netdata) — GPL / EPL — distributing a derived work obliges you to release its source under the same terms. Fine for internal use; plan carefully before proprietary distribution.
- Network copyleft (grafana, openobserve) — AGPL / SSPL — the copyleft trigger extends to offering the software over a network, so a hosted deployment of a modified version can oblige you to publish your changes. Read the exact terms before building a paid hosted product on these.
- Unverified license (signoz) — GitHub returned no clear SPDX id. Treat as all-rights-reserved until you read the project's LICENSE file directly — do not assume commercial use is permitted.
License fields come from the GitHub API's SPDX classification and can lag a relicense. The repository linked on each card is authoritative — confirm its LICENSE file before any license-sensitive deployment.
Maintenance health of these 5 projects
Of the 5 projects listed, 5 shipped at least one commit in the last 12 months. See how we rank for the full criteria and our self-hosting cost reality check, which apply across every comparison on this site.
Frequently asked questions
How do these 5 alternatives compare on maintenance health?
5 of 5 have shipped a commit in the last 12 months. At least one project here has 5,000+ GitHub stars, which usually correlates with sustained maintainership. Always check the last-pushed date in the cards above and read the latest 5 closed issues — those two signals together catch 80% of abandoned-project cases.
How this page was compiled
- Repository facts (stars, license, language, last commit) come straight from the GitHub public API and are linked on each card as the primary source.
- Editorial analysis is drafted from Datadog's use case and the alternatives' repository metadata, then reviewed by hand.
- Maintenance signal: 5 of 5 projects shipped a commit in the last 12 months as of the latest rebuild (most recent activity: ).
- Last editorial review: by Yusuke Morinaga.
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