SigNoz vs OpenObserve

SigNoz and OpenObserve both promise the same escape hatch: stop paying Datadog or Splunk by the gigabyte and run your own logs, metrics, and traces instead. Both are genuinely OpenTelemetry-native, so the instrumentation side of the decision is a wash — point your OTLP exporters at either one and they just work. The real choice is about how much platform you want to run and how much RAM you are willing to give it.

OTel-native platform vs. featherweight single binary

SigNoz is the fuller product. It ships as a multi-container stack — a Go/ TypeScript application backed by ClickHouse for storage, plus a bundled OpenTelemetry Collector that applications send data to on the usual OTLP ports. That collector-in-front architecture is what lets SigNoz do deep trace-to-log correlation, service maps, and RED metrics well; it is built first as an APM and distributed-tracing tool, with logs and metrics as first-class but secondary citizens. Its core is MIT-licensed — though it is open-core, with enterprise SSO and RBAC behind a paid tier — and it wants a realistic 4 GB of RAM, and installs at a 4 out of 5 difficulty — you are standing up a small stack, not dropping in a binary.

OpenObserve takes the opposite bet: it is a single Rust binary with its own embedded storage engine, no ClickHouse or Elasticsearch anywhere in sight. Logs, metrics, traces, dashboards, alerts, and even frontend RUM all live behind one process and one query layer. It accepts OTLP over HTTP and gRPC directly, so in the common case you don't need a separate collector at all. It rates a 512 MB floor and a 2 out of 5 difficulty — genuinely one of the lightest full observability stacks you can self-host. It is AGPL-3.0 licensed, the usual trade-off for software this featured and this free.

Footprint and resources

This is the starkest difference between them. SigNoz's ClickHouse-backed stack wants real memory to stay comfortable — 4 GB is the practical floor, and it climbs from there as retention and cardinality grow. OpenObserve's Parquet-based engine is built to sip resources: 512 MB is enough to get a working instance up, and even a modest VPS has headroom left over for the applications you're actually monitoring. If your box is small or you're watching a handful of services, that gap is the whole ballgame.

Signals and OTel support

Neither platform makes you choose a lane on signal types — both take logs, metrics, and traces, and both speak OTLP natively. The difference is in depth and defaults. SigNoz's bundled collector gives you a well-trodden path for protocol translation and enrichment before data lands in ClickHouse, and its query builder is tuned for correlating a slow trace with the logs and metrics around it. OpenObserve accepts OTLP directly with no collector required for the common case, and adds frontend RUM and session replay to the signal mix — a category SigNoz doesn't cover. If browser-side monitoring matters to you, OpenObserve has it built in; if deep backend trace correlation is the priority, SigNoz's tooling is more purpose-built for it.

Features and maturity

SigNoz is the more complete APM product today. Service maps, exceptions tracking, Apdex scoring, and a dashboard/alerting layer that spans application, infrastructure, and custom metrics are all mature, well-documented, and backed by a large, active community and a steady release cadence. OpenObserve's feature list is broader on paper (logs, metrics, traces, RUM, pipelines, even LLM-observability hooks), but it trades some of that APM depth — the service-map and trace-correlation polish SigNoz has invested years into — for operational simplicity and ingest-side efficiency. Both are actively developed; SigNoz is simply further along as a dedicated APM and tracing tool, while OpenObserve is optimizing for "one binary, one place to look, cheap to keep forever."

Storage engine

The storage choice explains almost every other difference. SigNoz leans on ClickHouse, a serious columnar analytics database that scales well and powers SigNoz's flexible query builder (including raw ClickHouse SQL for power users) — but it is another service to run, tune, and back up, and it is the main reason SigNoz's memory floor is what it is. OpenObserve rolls its own engine on Apache Parquet with a DataFusion query layer, purpose-built for cheap, long-retention storage of high-volume telemetry. There's no separate database to operate; the trade-off is a less battle-tested query surface than ClickHouse's decade of production hardening.

Upkeep

SigNoz is multi-container by nature — the app, its collector, and ClickHouse each have their own health to watch and their own data to protect, and ClickHouse in particular benefits from someone paying attention as volume grows. OpenObserve's single-binary model means there's fundamentally less to keep alive: one process, one data directory, one thing to back up. Neither is fragile day to day, but if "deploy it and mostly forget it" is the goal, OpenObserve is the lower-maintenance pick by a wide margin.

Which should you self-host?

Pick SigNoz if you want the more mature, more complete observability platform — deep APM, service maps, and trace correlation that rival the commercial tools you're replacing — and you're comfortable giving ClickHouse several gigabytes of RAM and a little ongoing attention. It's the stronger overall product and the safer default if you're not sure yet how deep your observability needs will go.

Pick OpenObserve if the priority is the lightest, cheapest-to-run option: a single binary that starts on 512 MB, needs almost no operational babysitting, and still covers logs, metrics, traces, and RUM in one place. It's the pick for small VPS instances, side projects, or anyone who wants a real OTel-native stack without paying for it in RAM or maintenance time.