GreptimeTeam / greptimedb

One database for metrics, logs, and traces replacing Prometheus, Loki, and Elasticsearch > The unified OpenTelemetry backend — with SQL + PromQL on object storage. User Guide | API Docs | Roadmap 2026 • Introduction • ⭐ Key Features • How GreptimeDB Compares • Architecture • Try GreptimeDB • Getting Started • Build From Source • Tools & Extensions • Project Status • Community • License • Commercial Support • Contributing • Acknowledgement Introduction **GreptimeDB** is an open-source observability database built for Observability 2.0 — treating metrics, logs, and traces as one unified data model (wide events) instead of three separate pillars. Use it as the single OpenTelemetry backend — replacing Prometheus, Loki, and Elasticsearch with one database built on object storage. Query with SQL and PromQL, scale without pain, cut costs up to 50x. Features | Feature | Description | | --------- | ----------- | | Drop-in replacement | PromQL, Prometheus remote write, Jaeger, and OpenTelemetry native. Use as your single backend for all three signals, or migrate one at a time.| | 50x lower cost | Object storage (S3, GCS, Azure Blob etc.) as primary storage. Compute-storage separation scales without pain.| | SQL + PromQL | Monitor with PromQL, analyze with SQL. One database replaces Prometheus + your data warehouse.| | Sub-second at PB-EB scale | Columnar engine with fulltext, inverted, and skipping indexes. Written in Rust.| ✅ **Perfect for:** • Replacing Prometheus + Loki + Elasticsearch with one database • Scaling past Prometheus — high cardinality, long-term storage, no Thanos/Mimir overhead • Cutting observability costs with object storage (up to 50x savings on traces, 30% on logs) • AI/LLM observability — store and analyze high-volume conversation data, agent traces, and token metrics via OpenTelemetry GenAI conventions • Edge-to-cloud observability with unified APIs on resource-constrained devices > **Why Observability 2.0?** The three-pillar model (separate databases for metrics, logs, traces) creates data silos and operational complexity. GreptimeDB treats all observability data as timestamped wide events in a single columnar engine — enabling cross-signal SQL JOINs, eliminating redundant infrastructure, and naturally supporting emerging workloads like AI agent observability. Read more: Observability 2.0 and the Database for It. Learn more in Why GreptimeDB. How GreptimeDB Compares | Feature | GreptimeDB | Prometheus / Thanos / Mimir | Grafana Loki | Elasticsearch | |---|---|---|---|---| | Data types | Metrics, logs, traces | Metrics only | Logs only | Logs, traces | | Query language | SQL + PromQL | PromQL | LogQL | Query DSL | | Storage | Native object storage (S3, etc.) | Local disk + object storage (Thanos/Mimir) | Object storage (chunks) | Local disk | | Scaling | Compute-storage separation, stateless nodes | Federation / Thanos / Mimir — multi-component, ops heavy | Stateless + object storage | Shard-based, ops heavy | | Cost efficiency | Up to 50x lower storage | High at scale | Moderate | High (inverted index overhead) | | OpenTelemetry | Native (metrics + logs + traces) | Partial (metrics only) | Partial (logs only) | Via instrumentation | **Benchmarks:** • GreptimeDB tops JSONBench's billion-record cold run test • TSBS Benchmark • More benchmark reports Architecture GreptimeDB can run in two modes: • **Standalone Mode** - Single binary for development and small deployments • **Distributed Mode** - Separate components for production scale: • Frontend: Query processing and protocol handling • Datanode: Data storage and retrieval • Metasrv: Metadata management and coordination Read the architecture document. DeepWiki provides an in-depth look at GreptimeDB: Try GreptimeDB Dashboard: http://localhost:4000/dashboard Read more in the full Install Guide. **Troubleshooting:** • Cannot connect to the database? Ensure that ports , , , and are not blocked by a firewall or used by other services. • Failed to start? Check the container logs with for further details. Getting Started • Quickstart • User Guide • Demo Scenes • FAQ Build From Source **Prerequisites:** • Rust toolchain (nightly) • Protobuf compiler (>= 3.15) • C/C++ building essentials, including / / and glibc library (eg. on Ubuntu and on Fedora) • Python toolchain (optional): Required only if using some test scripts. **Build and Run:** Tools & Extensions • **Kubernetes**: GreptimeDB Operator • **Helm Charts**: Greptime Helm Charts • **Dashboard**: Web UI • **gRPC Ingester**: Go, Java, C++, Erlang, Rust, .NET • **Grafana Data Source**: GreptimeDB Grafana data source plugin • **Grafana Dashboard**: Official Dashboard for monitoring Project Status > **Status:** RC — marching toward v1.0 GA! > **GA (v1.0):** March 2026 • Deployed in production handling billions of data points daily • Stable APIs, actively maintained, with regular releases (version info) GreptimeDB v1.0 represents a major milestone toward maturity — marking stable APIs, production readiness, and proven performance. **Roadmap:** v1.0 highlights and release plan and 2026 roadmap. For production use, we recommend using the latest stable release. If you find this project useful, a ⭐ would mean a lot to us! Community We invite you to engage and contribute! • Slack • Discussions • Official Website • Blog • LinkedIn • X (Twitter) • YouTube License GreptimeDB is licensed under the Apache License 2.0. Commercial Support Running GreptimeDB in your organization? We offer enterprise add-ons, services, training, and consulting. Contact us for details. Contributing • Read our Contribution Guidelines. • Explore Internal Concepts and DeepWiki. • Pick up a good first issue and join the #contributors Slack channel. Acknowledgement Special thanks to all contributors! See AUTHORS.md. • Uses Apache Arrow™ (memory model) • Apache Parquet™ (file storage) • Apache DataFusion™ (query engine) • Apache OpenDAL™ (data access abstraction)