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OpenObserve

Open-source, cloud-native observability platform written in Rust with Apache Parquet columnar storage and S3-native architecture — positioned as a 140x cheaper alternative to Elasticsearch.

Overview

OpenObserve (O2) is a high-performance observability platform built in Rust that provides unified logs, metrics, traces, and Real User Monitoring (RUM). Its architecture is built around Apache Parquet columnar storage on object storage (S3/GCS/Azure Blob), eliminating the need for local SSD clusters. It uses the Apache Arrow DataFusion query engine and supports SQL for logs/traces and PromQL for metrics.

Repository & Community

Attribute Detail
Repository github.com/openobserve/openobserve
Stars ~18.5k ⭐
Latest Version v0.70.3 stable / v0.80.0-rc3 pre-release (April 2026)
Language Rust
License AGPL-3.0 (copyleft)
Company OpenObserve, Inc.
Contributors ~109

Evaluation

  • Why it's better: Written in Rust (no GC, no JVM), Parquet columnar storage on S3 delivers 140x lower storage costs vs Elasticsearch, single-binary deployment, SQL as the primary query language (lower learning curve), stateless node architecture for effortless horizontal scaling, and built-in RBAC/SSO for enterprise readiness.

  • When it fits (Applicability):

  • Elasticsearch/ELK replacement (logs-heavy workloads)
  • Cost-conscious organizations with petabyte-scale log volumes
  • Teams wanting SQL-based observability queries
  • Cloud-native environments with S3/GCS object storage

  • Organizations needing RBAC/SSO out of the box

  • Pros and Cons:

Pros Cons
Rust: no GC pauses, excellent performance AGPL-3.0 license (copyleft restrictions)
140x cheaper storage vs Elasticsearch Pre-1.0 version, still maturing
Single binary deployment Smaller community than Grafana/SigNoz
SQL for logs/traces (low learning curve) No eBPF auto-instrumentation
S3-native (infinite storage) Less mature trace analysis than Tempo/Jaeger
Built-in RBAC and SSO Limited PromQL (metrics only)
Stateless horizontal scaling Fewer integrations/dashboards than Grafana
RUM / Frontend monitoring DataFusion query engine less battle-tested

Architecture

flowchart TB
    subgraph Ingestion["Data Sources"]
        OTEL_O["OTel Collector"]
        PROM_O["Prometheus"]
        FB_O["FluentBit /<br/>Vector"]
        SDK_O["RUM SDK"]
    end

    subgraph O2["OpenObserve Cluster"]
        direction TB
        Router["Router<br/>(request dispatch)"]
        Ingester["Ingester<br/>(→ Parquet)"]
        Querier["Querier<br/>(DataFusion)"]
        Compactor["Compactor<br/>(file merging)"]
        AlertMgr["AlertManager"]
    end

    subgraph Storage_O["Storage"]
        S3["S3 / GCS /<br/>Azure Blob / MinIO"]
        Parquet["Apache Parquet<br/>columnar format"]
    end

    Ingestion --> Router --> Ingester
    Ingester --> Parquet --> S3
    Querier --> S3
    Compactor --> S3
    AlertMgr --> Querier

    style O2 fill:#e65100,color:#fff
    style Storage_O fill:#1565c0,color:#fff

Key Components

Component Role
Router Dispatches incoming requests to appropriate component
Ingester Receives telemetry, converts to Parquet, writes to object storage
Querier Apache Arrow DataFusion engine: SQL/PromQL queries on Parquet
Compactor Merges small Parquet files for query efficiency
AlertManager Manages alert queries, report jobs, notifications

Key Features

Feature Detail
Unified Logs, Metrics, Traces All signals in one platform
Real User Monitoring (RUM) Core Web Vitals, page load, client errors
SQL Queries Standard SQL for logs and traces
PromQL Prometheus-compatible metrics queries
Dashboards Drag-and-drop, customizable panels
Alerting Multi-signal alerts, notification pipelines
Pipelines Ingestion-time data transformation
RBAC & SSO Built-in enterprise access controls
Compliance ISO 27001, SOC 2, GDPR ready
Single Binary Trivial deployment for POC/dev

Pricing

Tier Cost Notes
Self-Hosted (Free) $0 (AGPL-3.0) Full features, manage your own infra
Cloud - Developer Free 200 GB ingestion, 15 day retention
Cloud - Pro Usage-based (~$0.60/GB) Logs, metrics, traces
Enterprise Custom Commercial license, SLA, audit logs

Compatibility

Dimension Support
Ingestion protocols OTLP (gRPC + HTTP), Prometheus remote_write, ES Bulk API, Kinesis Firehose, GCP Pub/Sub
Query languages SQL (logs/traces), PromQL (metrics)
Storage backends S3, GCS, Azure Blob, MinIO (Parquet format)
Deployment Single binary, Docker, Kubernetes (Helm), OpenObserve Cloud
CPU architecture amd64, arm64
Platforms Linux, macOS, Windows

Sources