OpenObserve
Open-source observability at petabyte scale with 140x lower storage cost
Founded
2022
Starting Price
Free
Category
Monitoring & Observability
Last updated March 23, 2026
About OpenObserve
OpenObserve is an open-source, cloud-native observability platform that unifies logs, metrics, traces, real user monitoring, and dashboards into a single tool. Built in Rust with Apache Parquet columnar storage, it delivers up to 140x lower storage cost compared to Elasticsearch and Splunk while supporting petabyte-scale ingestion. It is OpenTelemetry-native, deploys in under 2 minutes, and is trusted by 6,000+ organizations.
Pros & Cons
Pros
- Dramatically lower cost at 140x cheaper storage than Elasticsearch and Splunk
- Truly unified platform for logs, metrics, traces, RUM, and session replay
- Fast deployment with single binary operational in under 2 minutes
- Open standards with OpenTelemetry native support and SQL/PromQL queries
- Proven at scale with largest deployments exceeding 2 PB per day
Key Features
Unified Observability
Single platform for logs, metrics, traces, RUM, error tracking, and session replay
140x Lower Storage Cost
Apache Parquet columnar format with 40x compression versus Elasticsearch
OpenTelemetry Native
Full OTLP support and first-class OpenTelemetry compatibility with no vendor lock-in
Real User Monitoring
Frontend performance monitoring, session replay, JavaScript error tracking, and Core Web Vitals
Data Pipelines
Real-time stream processing for log enrichment, data redaction, and multi-destination routing
SQL & PromQL Queries
Query logs with SQL and metrics with PromQL using standard languages
High Availability & Clustering
Stateless, horizontally scalable architecture supporting 2+ PB/day deployments
Pricing
Free Trial
Free
- 14-day trial
- Full Pay As You Go features
- Cloud-hosted
Pay As You Go
\u00240.50/GB ingested
Best For
Kubernetes Infrastructure Monitoring
Monitor pods, nodes, and cloud resources with unified metrics and logs
Microservices Distributed Tracing
Visualize request flows across services with flamegraphs to identify latency bottlenecks
Cost Migration from Datadog/Splunk
Drop-in replacement for expensive observability stacks with 80-140x cost reduction
Frontend Performance Monitoring
Capture Core Web Vitals, session replays, and JavaScript errors from real users
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Best for log-heavy workloads where storage cost is the primary concern, with the easiest single-binary deployment of any unified observability platform
#2
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Best for maximum cost reduction — if your Datadog bill is dominated by log storage and data retention costs, OpenObserve's compression technology delivers the biggest savings.
