At a glance — how these 8 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 |
|---|---|---|---|
| ★ 80,656 · Go GPL-3.0 | Flagship | Active | High risk Distributing a derived work obliges releasing its source |
| ★ 76,914 · TypeScript AGPL-3.0 | Flagship | Active | High risk Even a hosted/modified deployment can trigger source release |
| ★ 66,231 · Go Apache-2.0 | Flagship | Active | Low risk Embed in a proprietary product with no copyleft obligation |
| ★ 32,199 · TypeScript | Flagship | Active | Low risk Embed in a proprietary product with no copyleft obligation. Split licence — this rates the core component; read the † text for the separately licensed parts |
| ★ 28,946 · Go AGPL-3.0 | Mainstream | Active | High risk Even a hosted/modified deployment can trigger source release |
| ★ 22,133 · TypeScript AGPL-3.0 | Mainstream | Active | High risk Even a hosted/modified deployment can trigger source release |
| ★ 9,913 · TypeScript MIT | Mainstream | Active | Low risk Embed in a proprietary product with no copyleft obligation |
| ★ 5,488 · Go AGPL-3.0 | Mainstream | Active | High risk Even a hosted/modified deployment can trigger source release |
† Licenses marked † were read from the repository's LICENSE file on 2026-09-05 (linked, pinned to the commit we read) because the GitHub API returned no SPDX id for them. Unmarked licenses are the GitHub API's SPDX classification.
The alternatives
netdata
The fastest path to AI-powered full stack observability, even for lean teams.
netdata/netdata Updated 2026-09-26 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 2026-09-26 prometheus
The Prometheus monitoring system and time series database.
prometheus/prometheus Updated 2026-09-25 SigNoz is an open-source, OpenTelemetry-native observability platform for your team and their AI agents. Get logs, metrics, and traces in one tool with features like APM, distributed tracing, log management, infra monitoring, etc. Combined with SigNoz MCP and a native AI teammate (in SigNoz Cloud) it helps you build more resilient apps.
SigNoz/signoz Updated 2026-09-26 loki
Like Prometheus, but for logs.
grafana/loki Updated 2026-09-26 openobserve
Open source observability platform for logs, metrics, traces, RUM (web, android, ios), Session replay, pipelines, SLO 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 2026-09-26 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 2026-09-25 tempo
Grafana Tempo is a high volume, minimal dependency distributed tracing backend.
grafana/tempo Updated 2026-09-25 Editor's take
Yusuke Morinaga · last revisited · star counts quoted in the text (≈) are as of that date; the cards above are refreshed daily
The Datadog alternatives above solve different shapes of the observability problem — a project-by-project read of where each actually fits.
The list above reads like a row of interchangeable swap-outs for Datadog. They are not. To be upfront about method: I have not operated these in production — what follows is a close reading of their architectures, docs, and the incident write-ups and migration threads their communities publish, checked against the repo data on this page. Each project solves a different shape of the observability problem, and the cost of picking wrong is months of re-instrumentation. Here is the project-by-project read.
Netdata — ≈80.4k★, but the star count flatters it
Netdata has the most stars of the eight projects here, 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 any single project above — it is four of the cards run together: Grafana as the UI layer, Prometheus for metrics, and Grafana’s own Loki for logs and Tempo for traces. 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 dedicated 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 (≈9.9k★), 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
Replacing Datadog means assembling a stack rather than dropping in one tool. Grafana paired with Prometheus handles metrics and dashboards at scale; OpenTelemetry feeding Tempo covers distributed tracing; and Loki takes care of log aggregation. That assembly is the cost — you wire these together and run your own storage backends, where Datadog quietly manages retention, scaling, and querying for you. Two specifics worth knowing: matching Datadog's automatic APM instrumentation and cross-service flame graphs takes a fair amount of hand-tuned OpenTelemetry config, and its security monitoring, CSPM, and log anomaly detection have no open-source equivalent at the same level of 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?
Replacing Datadog isn't a single call — it's a trade between license terms, team size, and how much early-stage roughness you can absorb. The 8 projects above split along those lines:
- You want the project with the most GitHub stars in this list → netdata. 80,656★ — but grafana is close behind at 76,914★, so treat the two as equals on this signal and decide on license and fit instead.
- You ship commercial software and need to ship modified code without releasing source → prometheus. Apache-2.0 licensed — modify and embed without copyleft obligations.
- You want the project with the most recent push activity → loki. Last push 2026-09-26 — the freshest activity in this list.
License & commercial-use notes
When replacing Datadog, the license usually decides more than the feature list — whether you can modify it, ship it inside a product, or host it as a service. The 8 projects here fall into:
- Permissive (prometheus, signoz, 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, loki, openobserve, tempo) — 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.
Split licences: signoz (MIT (core) + separate license for ee/ and cmd/enterprise/). This project is grouped above by the core licence; the separately licensed directories (enterprise or EE parts) are not covered by that bucket — check which files you actually ship.
License fields come from the GitHub API's SPDX classification and can lag a relicense. Where the API returned no SPDX id, the license marked † was read from the repository's LICENSE file on 2026-09-05; the † links to the exact file and commit we read. The repository linked on each card is authoritative — confirm its LICENSE file before any license-sensitive deployment.
Maintenance health of these 8 projects
Of the 8 projects listed, 8 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 8 alternatives compare on maintenance health?
8 of 8 have shipped a commit in the last 12 months. At least one project here has 5,000+ GitHub stars. Always check the last-pushed date in the cards above and read the latest closed issues — those two signals are the fastest public check we know of.
How this page was compiled
- Repository facts (stars, license, language, last push) come straight from the GitHub public API and are linked on each card as the primary source. Where the API returned no SPDX id, the licence marked † was read from the repository's
LICENSEfile (linked, pinned to the commit we read, with the date checked). - Editorial analysis (the intro, comparison notes and migration tips) is Claude-drafted from Datadog's use case and the alternatives' repository metadata — in Claude Code sessions or scheduled routines run under the operator's account. Samples are spot-checked against the upstream repositories; entries are not individually reviewed unless they carry a signature. See what Claude drafts and what the operator writes.
- Editor's take is signed by Yusuke Morinaga. It was drafted in a Claude Code session the operator ran, then read and confirmed by Yusuke Morinaga before publication, and carries the date it was last revised. It is written from each project's README, LICENSE, release history and issue tracker — not from running the project in production; where that distinction matters, the take says so.
- Maintenance signal: 8 of 8 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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