SigNoz vs Elastic Observability
A detailed comparison to help you choose between SigNoz and Elastic Observability.
Quick Verdict
4.8/5
SigNoz
329 reviews
4.1/5
Elastic Observability
249 reviews
SigNoz is rated higher (4.8 vs 4.1). SigNoz is a full-stack open source observability platform — metrics, traces, and logs in one. Datadog alternative you can self-host. Uses ClickHouse for efficient storage. Unified observability platform that collects and analyzes metrics, logs, and traces from servers, applications, and services. Built for DevOps teams managing complex distributed systems.
SigNoz Open-source observability platform for logs, metrics, and traces | Elastic Observability Real-time visibility into infrastructure, applications, and logs | |
|---|---|---|
| Overview | ||
| Rating | 4.8 (329 reviews)✓ | 4.1 (249 reviews) |
| Pricing model | freemium | freemium |
| Starting price | Free tier available | Free tier available |
| Best for | Engineering teams seeking production observability without vendor lock-in or high costs, especially those comfortable managing self-hosted infrastructure. | Engineering teams running Elasticsearch who need consolidated observability without additional tool licensing and can manage operational complexity. |
| Tags | ||
| Tags | free tieropen sourceself hostableapi access | free tieropen sourceself hostableapi accessteam features |
| Visit SigNoz → | Visit Elastic Observability → | |
SigNoz
Pros
- + Consolidate logs, metrics, and traces in one interface
- + Deploy on your own infrastructure for data privacy and cost control
- + Built on OpenTelemetry standards for vendor independence
- + Offers alerting and anomaly detection without extra fees
- + Reduce observability costs by 60-80% versus commercial alternatives
Cons
- - Smaller ecosystem and fewer integrations compared to DataDog
- - Self-hosted deployment requires infrastructure maintenance and expertise
- - Community support instead of dedicated enterprise SLAs
Elastic Observability
Pros
- + Ingest high-volume metrics and logs without separate monitoring licenses
- + Query logs and metrics using the same Kibana interface
- + Pre-built dashboards and integrations for common platforms and services
- + Correlate infrastructure metrics with application traces for faster troubleshooting
Cons
- - Steep learning curve for Elasticsearch Query DSL and Kibana configuration
- - Self-managed deployments require significant infrastructure and operational overhead
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