OpenObserve
OpenObserve unifies logs, metrics, traces, and RUM in one open source platform. Up to 140x lower cost than Elasticsearch. OpenTelemetry native. Try free.
Editor's Verdict
Key Takeaways
- Unified Observability
- Open Source
- Cost-Effective Storage
- High Performance
In-Depth Review: What is OpenObserve?
OpenObserve is a modern, open source observability platform that unifies logs, metrics, traces, and Real User Monitoring (RUM) into a single solution. Built for performance and efficiency, it leverages Apache Parquet columnar storage to achieve up to 140x lower storage costs than Elasticsearch and 8-10x lower total cost than Datadog. With native OpenTelemetry support, SQL and PromQL query languages, and a single binary deployment, OpenObserve eliminates tool fragmentation and vendor lock-in. Trusted by over 8,000 organizations from startups to Fortune 500 companies, it provides petabyte-scale scalability, blazing fast query performance (1 petabyte in 2 seconds), and a built-in AI SRE agent. Deploy on-premises or in the cloud with your own storage (S3, GCS, Azure Blob). Get started with a free trial or join the upcoming webinar on July 30, 2026.
Core Features
Unified Observability
Combines logs, metrics, traces, and real user monitoring (RUM) into a single platform, eliminating the need for multiple tools.
Open Source
Fully open source under AGPL-3.0 license, allowing community contributions, security audits, and complete control over data.
Cost-Effective Storage
Uses Apache Parquet columnar storage with ~40x compression, achieving up to 140x lower storage costs compared to Elasticsearch.
High Performance
Built with Rust and DataFusion query engine, capable of querying 1 petabyte of data in under 2 seconds.
Scalable Architecture
Stateless node design allows horizontal scaling without data complexity, supporting petabyte-scale deployments.
Open Standards Support
Native OpenTelemetry, SQL, and PromQL support ensures no vendor lock-in and seamless integration with existing tools.
AI-Powered Insights
Built-in AI SRE Agent for automated root cause analysis and natural language querying, reducing mean time to resolution.
Flexible Deployment
Deploy as a single binary or Helm chart on any infrastructure: self-hosted, public cloud, or bring your own cloud.
Pricing
Professional (Cloud)
- Logs, Metrics, Traces, RUM, Session Replay, Error Tracking
- 30-day retention for non-metrics data
- 15-month retention for metrics
- 14-day free trial
Enterprise (Cloud)
- All Professional features
- Additional retention for non-metrics data
- Pipelines and Sensitive Data Redaction
- AI-Powered Observability and AI SRE Agent
- Incident Management
- AI Assistant
- Audit Trail
- Unlimited Users
- Single Sign-On (SSO)
- Role-Based Access Control (RBAC)
- Premium Support
- Deployment flexibility
- Architecture reviews
- Volume discounts
- SLAs
Self-Hosted Enterprise
- SSO, RBAC, Audit Trail
- All core observability features
- Unlimited users
- Volume discounts available
Pros and Cons
Pros
- Cost SavingsUp to 140x lower storage costs than Elasticsearch and 8-10x lower total cost than Datadog, with flat per-GB ingestion pricing and unlimited users.
- Unified PlatformCombines logs, metrics, traces, and RUM in one tool with one query language (SQL/PromQL), eliminating multi-tool fragmentation.
- Open Source & Vendor NeutralFully open source, AGPL-3.0 licensed, with native OpenTelemetry support ensures no lock-in and transparent development.
- High PerformanceBuilt with Rust and DataFusion, enabling fast queries (1 PB in 2 seconds) and efficient resource usage.
- ScalabilityStateless architecture allows horizontal scaling to petabyte-scale without data complexity, proven in Fortune 100 environments.
Cons
- Learning Curve for MigrantsUsers coming from Grafana or Datadog may need time to adapt to OpenObserve's unique query interface and concepts.
- Limited Free Tier FeaturesThe free self-hosted tier (up to 50 GB/day) lacks advanced features like SSO, RBAC, and audit trail, which require Enterprise plan.
- Relatively Newer in MarketCompared to established vendors like Datadog or Splunk, OpenObserve has a smaller ecosystem and fewer third-party integrations.
- Self-Hosted Operational OverheadRunning OpenObserve on-premises or on your own cloud requires management of infrastructure, upgrades, and backups.
- Usage-Based Pricing VariabilityCosts are tied to ingestion volume, which can be unpredictable for peak loads, though flat per-GB pricing helps.
Use Cases & Recommended Professions
DevOps Engineer→ View Toolkit
Needs a unified observability platform to monitor microservices and infrastructure without managing multiple tools.
Site Reliability Engineer (SRE)→ View Toolkit
Requires high-performance, cost-effective monitoring for incident response and root cause analysis.
Platform Engineer→ View Toolkit
Benefits from an open-source, scalable observability stack that integrates with existing infrastructure.
Software Engineer→ View Toolkit
Uses logs, traces, and metrics to debug applications and optimize performance in development and production.
CTO/VP of Engineering→ View Toolkit
Seeks to reduce observability costs and simplify tooling across the organization.
IT Operations Manager→ View Toolkit
Needs a unified view of system health, alerts, and user experience to ensure uptime and SLAs.
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ℹ️ Curation Disclosure: The overview and features of OpenObserve were synthesized using AI and fact-checked by our curation team to ensure accuracy.