OpenObserve
UnclaimedOpen source, petabyte-scale observability for logs, metrics, and traces at a fraction of the cost.
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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Paid plans only
Biggest pro
Significantly lower storage costs (up to 140x compared to Elasticsearch).
Biggest con
Pricing for advanced features like AI Assistant and AI SRE Agent is currently in preview, future costs are not fully detailed.
TL;DR - OpenObserve
- Open-source observability for logs, metrics, and traces.
- Achieves 140x lower storage cost and petabyte-scale performance.
- Offers unified data correlation for faster root cause analysis.
Pricing: Paid only
Best for: Enterprises & pros
What is OpenObserve?
OpenObserve is an open-source observability platform designed to help organizations of all sizes, from Fortune 500 giants to innovative startups, manage their logs, metrics, and traces efficiently and cost-effectively. It provides a unified platform for comprehensive visibility into infrastructure performance, health, and resource utilization, enabling faster root cause analysis and reduced mean time to resolution (MTTR).
The platform is built with a modern, scalable architecture in Rust, utilizing the DataFusion query engine for high performance and low cost. It supports petabyte-scale data ingestion and querying, offering significant storage cost reductions through high compression and columnar storage with Apache Parquet. OpenObserve is compatible with OpenTelemetry and other industry standards, ensuring interoperability with existing tools and workflows. It offers both cloud-hosted and self-hosted deployment options, allowing users to bring their own storage buckets like S3, MinIO, GCS, and Azure Blob Storage.
Available on: Web
Pros & Cons
Pros
- Significantly lower storage costs (up to 140x compared to Elasticsearch).
- High performance and scalability, capable of handling petabytes of data.
- Open-source nature allows for community contributions, security audits, and full control.
- Unified platform for logs, metrics, and traces simplifies observability.
- Supports open standards and protocols for vendor-neutral integration.
Cons
- Pricing for advanced features like AI Assistant and AI SRE Agent is currently in preview, future costs are not fully detailed.
- Requires some technical expertise for self-hosting and managing storage buckets.
Preview
Key Features
Logs, Metrics & Traces IngestionHigh Compression (40x) and Columnar Storage (Apache Parquet)Bring Your Own Storage (S3, MinIO, GCS, Azure Blob Storage)DataFusion Query Engine for direct Parquet file queryingStateless Node Architecture for horizontal scalingResult and Disk Caching for performance at scaleOpenTelemetry compatibleReal User Monitoring (RUM)
Pricing Plans
Free TrialPricing checked Jun 11, 2026
Pay As You Go
Pay for what you use
Everything in all plans.
Enterprise
Contact Sales
Everything in all plans, plus:
- Premium support
- Deployment flexibility (Public Cloud, or Bring Your Own Cloud)
- Architecture reviews
- Volume discounts
Included in all plans
- Logs, Metrics & Traces Ingestion: $0.50 per GB
- Logs, Metrics & Traces Query: $0.01 per GB
- Pipelines Data processed: $0.20 per GB
- Pipelines Each additional destination: $0.30 per GB
- Real User Monitoring (RUM): $0.15 / 1K sessions
- Session Replay: $1.00 / 1K sessions
- Error Tracking: $0.15 / 1K events
- Sensitive Data Redaction: $0.15 / GB
Reviews
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OpenObserve FAQ
How does OpenObserve help reduce operational costs?
OpenObserve significantly lowers storage costs, offering up to 140x savings compared to alternatives like Elasticsearch. It achieves this through high compression and columnar storage using Apache Parquet, alongside its scalable architecture built in Rust.
Which teams benefit most from using OpenObserve?
DevOps teams and organizations focused on monitoring and log management will find OpenObserve particularly useful. It provides comprehensive visibility into infrastructure performance and resource utilization, aiding in faster root cause analysis.
How does OpenObserve compare to Datadog for observability?
OpenObserve provides a unified, open-source platform for logs, metrics, and traces, built for petabyte-scale data ingestion and querying. It offers significant storage cost reductions and supports open standards, unlike proprietary solutions.
What kind of technical expertise is needed to implement OpenObserve?
Implementing OpenObserve, especially for self-hosting, requires some technical expertise. Users need to manage their own storage buckets, such as S3, MinIO, GCS, or Azure Blob Storage, and understand the platform's configuration.
Does OpenObserve integrate with existing monitoring tools and data sources?
Yes, OpenObserve is compatible with OpenTelemetry and other industry standards, ensuring interoperability with existing tools and workflows. This allows for vendor-neutral integration across various data sources.
How is OpenObserve priced?
OpenObserve is a paid product, and it does not include a permanently free tier. Pricing for advanced features like the AI Assistant and AI SRE Agent is currently in preview.
Can OpenObserve handle large volumes of data for analysis?
Yes, OpenObserve is designed for petabyte-scale data ingestion and querying. Its modern, scalable architecture and use of the DataFusion query engine enable high performance even with massive datasets.
Source: openobserve.ai