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OpenObserve

OpenObserve

AI-native, open-source Datadog alternative

Website openobserve.ai
Overview

What it is

Fast, scalable and cost-effective open-source observability platform. Monitor logs, metrics & traces with 140x lower storage costs than ElasticSearch. Start in 2 minutes.

Intent

I need it when

Monitor logs, metrics, and traces in a single unified platform without managing multiple tools

OpenObserve unifies logs, metrics, traces, RUM, dashboards, alerts, and session replay in one platform with one query language (SQL and PromQL) and one storage layer. This eliminates fragmentation of multi-tool stacks like Grafana LGTM or ELK.

Deploy observability infrastructure with full data control and no vendor lock-in

OpenObserve is fully open source (AGPL-3.0), supports self-hosting on Kubernetes/Docker, uses standard OpenTelemetry, and stores data on bring-your-own object storage (S3, GCS, Azure Blob). Teams retain complete control over data residency and can migrate between cloud and self-hosted anytime.

Reduce observability infrastructure costs by 5-10x compared to Datadog or Splunk

OpenObserve charges $0.50/GB ingestion with no per-host or per-seat fees and includes unlimited users. Cloud plans include 30% annual discount. Self-hosted enterprise is free up to 50 GB/day. This directly addresses cost-conscious teams migrating from expensive SaaS platforms.

Automate incident detection and root-cause analysis using AI without separate tools

OpenObserve includes AI SRE Agent (free during preview with 20 credits) that correlates alerts into incidents, identifies root causes, and provides remediation suggestions. AI Assistant converts natural language to SQL/PromQL. This reduces alert fatigue and replaces need for separate incident management tools.

Query and analyze petabyte-scale observability data with sub-second response times

OpenObserve uses Rust, DataFusion query engine, Apache Parquet columnar storage with 40x compression, and result/disk caching. Benchmarks show 1 petabyte queries return in 2 seconds. This enables fast root-cause analysis at enterprise scale.

Drop

Not a fit when

  • Organization requires per-host or per-user pricing model instead of per-GB ingestion
  • Team needs proprietary query language and vendor lock-in with managed SaaS-only deployment
  • Use case requires sub-30-day data retention for logs and traces without additional costs
  • Organization cannot tolerate open source AGPL-3.0 licensing requirements
  • Workload involves less than 50 GB/day ingestion and needs zero operational overhead without self-hosting
Commercials

Pricing

Pay-as-you-go ingestion-based pricing for cloud; free self-hosted open source and enterprise editions View pricing