1
SigNoz
SigNoz offers a unified observability platform for logs, metrics, and traces with a ClickHouse backend, emphasizing OpenTelemetry native support.
AI Tool
OpenObserve Review
OpenObserve is an open-source observability platform for logs, metrics, and traces with 140x lower storage costs compared to Elasticsearch.
shipped Mar 19, 2026aifree
1Offers 140x lower storage costs than Elasticsearch through its Rust-based architecture and Apache Parquet columnar storage.
2Provides a unified platform for logs, metrics, traces, and Real User Monitoring (RUM) with OpenTelemetry compatibility.
3Secured $10 million in Series A funding in April 2026, launching 'Observability 3.0' with AI-native capabilities.
4Holds ISO 27001 and SOC 2 Type II certifications, with HIPAA readiness and BAA available for Enterprise contracts.
OpenObserve at a Glance
About OpenObserve
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2
Grafana Labs (Loki, Prometheus, Tempo)
Grafana Labs provides a modular, open-source stack (Loki for logs, Prometheus/Mimir for metrics, Tempo for traces) with Grafana as the visualization layer, offering maximum flexibility and a vast ecosystem.
3
OpenSearch
OpenSearch is an open-source search and analytics suite, forked from Elasticsearch, providing a robust platform for logs, metrics, and traces with a familiar interface.
4
Datadog
Datadog is a comprehensive SaaS-based observability platform offering extensive monitoring, APM, and security features across cloud-scale infrastructure and applications.
overview
What is OpenObserve?
OpenObserve is an observability platform developed by OpenObserve that enables DevOps and platform engineering teams to monitor logs, metrics, and traces with significantly lower storage costs. It unifies various telemetry data types into a single, cost-effective tool, supporting petabyte-scale data. The platform, founded in 2022 and headquartered in Paris, is built with Rust and utilizes Apache Parquet for efficient columnar storage. Recent developments include a $10M Series A funding round in April 2026 and the launch of 'Observability 3.0,' which introduced AI-native features such as an autonomous AI SRE Agent and LLM observability. OpenObserve is designed to provide comprehensive visibility for modern cloud-native applications, offering an alternative to both expensive SaaS solutions and complex, fragmented open-source stacks.
quick facts
Quick Facts
| Attribute | Value |
|---|---|
| Developer | OpenObserve |
| Business Model | Open-source core, Freemium (Self Hosted Enterprise), Usage-based (Cloud) |
| Pricing | OSS Plan: Free; Self Hosted Enterprise Plan: Free up to 200 GB/day ingestion; Cloud Plans: Ingestion based (per GB ingested) |
| Platforms | Self-hosted, Cloud (Web, API) |
| API Available | Yes |
| Integrations | OpenTelemetry, S3, MinIO, GCS, Azure Blob Storage, Kubernetes, Terraform |
| Founded | 2022 |
| HQ | Paris |
| Funding | $10M Series A (April 2026) |
features
Key Features of OpenObserve
OpenObserve provides a comprehensive suite of features for full-stack observability, designed to streamline monitoring and reduce operational overhead. Its architecture, based on Rust and Apache Parquet, ensures high performance and data compression. The platform supports a wide range of telemetry data and offers advanced capabilities for analysis and incident management.
- 1Logs, Metrics, and Traces monitoring for unified visibility across applications and infrastructure.
- 2Real User Monitoring (RUM) for tracking frontend performance, errors, and user sessions.
- 3Customizable Dashboards and Alerting capabilities with over 19 built-in chart types for proactive incident detection.
- 4AI SRE Agent for automated root cause analysis and natural language querying, introduced with Observability 3.0.
- 5OpenTelemetry compatibility for native ingestion of telemetry data, ensuring broad ecosystem integration.
- 6Multi-organization isolation, Single Sign-On (SSO), and Role-Based Access Control (RBAC) for enterprise-grade security and management.
- 7High data compression (~40x) using Apache Parquet columnar storage, contributing to 140x lower storage costs.
- 8Support for various object storage solutions including S3, MinIO, GCS, and Azure Blob Storage, with Bring Your Own Bucket (BYOB) for Cloud offerings.
- 9SQL and PromQL query language support for flexible data analysis and compatibility with existing monitoring tools.
- 10Terraform provider and Kubernetes module for infrastructure-as-code management and simplified deployment on Kubernetes.
use cases
Who Should Use OpenObserve?
OpenObserve is primarily designed for technical teams seeking a unified, cost-effective, and scalable observability solution. Its open-source nature and focus on efficiency make it suitable for organizations looking to gain comprehensive insights into their systems without incurring high costs or managing complex, fragmented toolchains.
- 1DevOps and Platform Engineering teams requiring full-stack observability for modern cloud-native applications.
- 2Startups and Enterprises aiming for cost-effective monitoring of logs, metrics, and traces at petabyte scale.
- 3Organizations looking to replace expensive SaaS platforms like Datadog, Splunk, or New Relic to reduce vendor lock-in and unpredictable bills.
- 4Teams standardizing on OpenTelemetry for unified data collection and distributed tracing across microservices.
- 5Users needing real-time log data search, analysis, and incident correlation with customizable dashboards and alerting.
pricing
OpenObserve Pricing & Plans
OpenObserve offers a flexible pricing model designed to cater to various organizational needs, from individual developers to large enterprises. It includes a free open-source option, a freemium self-hosted enterprise plan, and an ingestion-based cloud offering.
- 1OSS Plan: Free for self-hosting, providing full access to the core platform with no usage limits.
- 2Self Hosted Enterprise Plan: Free up to 200 GB/day ingestion, includes advanced features such as SSO, RBAC, Audit trail, and Federated search for enhanced security and management.
- 3Cloud Plans: Ingestion-based pricing (per GB ingested), offering a 14-day free trial. Customers can receive a 30% discount for annual commitments and benefit from high volume discounts for Enterprise-level usage. The Cloud offering also supports Bring Your Own Bucket (BYOB) for data residency and compliance.
competitors
OpenObserve vs Competitors
OpenObserve positions itself as a modern, open-source observability platform that addresses the limitations of both expensive proprietary SaaS solutions and fragmented open-source stacks. It differentiates itself primarily through its extreme cost efficiency, unified architecture, and OpenTelemetry-native approach.
1
SigNoz↗
SigNoz offers a unified observability platform for logs, metrics, and traces with a ClickHouse backend, emphasizing OpenTelemetry native support.
Similar to OpenObserve in unifying telemetry and being OpenTelemetry-native, SigNoz is often noted for deeper tracing and APM capabilities, while OpenObserve focuses on extreme storage cost efficiency and simpler deployment.
2
Grafana Labs provides a modular, open-source stack (Loki for logs, Prometheus/Mimir for metrics, Tempo for traces) with Grafana as the visualization layer, offering maximum flexibility and a vast ecosystem.
OpenObserve offers a single, unified binary/platform for logs, metrics, and traces, aiming for simpler deployment and lower operational overhead compared to managing the multiple components of the Grafana LGTM stack.
3
OpenSearch is an open-source search and analytics suite, forked from Elasticsearch, providing a robust platform for logs, metrics, and traces with a familiar interface.
OpenObserve aims for significantly lower storage costs (140x less than Elasticsearch) and a unified SQL querying experience across all telemetry, whereas OpenSearch maintains compatibility with Elasticsearch's query DSL and architecture.
4
Datadog is a comprehensive SaaS-based observability platform offering extensive monitoring, APM, and security features across cloud-scale infrastructure and applications.
Datadog is a commercial, typically more expensive solution with a per-host/indexed log pricing model, while OpenObserve is an open-source, self-hostable alternative focused on drastically lower storage and operational costs through its architecture and ingestion-based pricing.
❓
Frequently Asked Questions
+What is OpenObserve?
OpenObserve is an observability platform developed by OpenObserve that enables DevOps and platform engineering teams to monitor logs, metrics, and traces with significantly lower storage costs. It unifies various telemetry data types into a single, cost-effective tool, supporting petabyte-scale data.
+Is OpenObserve free?
Yes, OpenObserve offers a free OSS Plan for self-hosting with no usage limits. Additionally, its Self Hosted Enterprise Plan is free up to 200 GB/day ingestion, including features like SSO and RBAC. Cloud Plans are ingestion-based with a 14-day free trial and discounts for annual commitments.
+What are the main features of OpenObserve?
Key features include unified monitoring for logs, metrics, traces, and Real User Monitoring (RUM), customizable dashboards and alerts, an AI SRE Agent for automated root cause analysis, OpenTelemetry compatibility, high data compression with Apache Parquet, and support for various object storage solutions. Enterprise features like SSO and RBAC are also available.
+Who should use OpenObserve?
OpenObserve is ideal for DevOps and Platform Engineering teams, startups, and enterprises seeking cost-effective, full-stack observability. It's particularly suited for organizations looking to standardize on OpenTelemetry, reduce monitoring costs compared to expensive SaaS platforms, or simplify complex self-managed open-source stacks.
+How does OpenObserve compare to alternatives?
OpenObserve differentiates itself by offering 140x lower storage costs than Elasticsearch and providing a unified platform for logs, metrics, and traces, unlike fragmented solutions like the Grafana LGTM stack. Compared to expensive SaaS providers like Datadog, OpenObserve offers an open-source, self-hostable alternative with predictable, ingestion-based pricing and full data control.
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