Delivers sub-second querying at PB scale and exceptional cost efficiency from edge to cloud.
- Introduction
- ⭐ Key Features
- Quick Comparison
- Architecture
- Try GreptimeDB
- Getting Started
- Build From Source
- Tools & Extensions
- Project Status
- Community
- License
- Commercial Support
- Contributing
- Acknowledgement
GreptimeDB is an open-source, cloud-native database purpose-built for the unified collection and analysis of observability data (metrics, logs, and traces). Whether you’re operating on the edge, in the cloud, or across hybrid environments, GreptimeDB empowers real-time insights at massive scale — all in one system.
Feature | Description |
---|---|
Unified Observability Data | Store metrics, logs, and traces as timestamped, contextual wide events. Query via SQL, PromQL, and streaming. |
High Performance & Cost Effective | Written in Rust, with a distributed query engine, rich indexing, and optimized columnar storage, delivering sub-second responses at PB scale. |
Cloud-Native Architecture | Designed for Kubernetes, with compute/storage separation, native object storage (AWS S3, Azure Blob, etc.) and seamless cross-cloud access. |
Developer-Friendly | Access via SQL/PromQL interfaces, REST API, MySQL/PostgreSQL protocols, and popular ingestion protocols. |
Flexible Deployment | Deploy anywhere: edge (including ARM/Android) or cloud, with unified APIs and efficient data sync. |
Learn more in Why GreptimeDB and Observability 2.0 and the Database for It.
Feature | GreptimeDB | Traditional TSDB | Log Stores |
---|---|---|---|
Data Types | Metrics, Logs, Traces | Metrics only | Logs only |
Query Language | SQL, PromQL, Streaming | Custom/PromQL | Custom/DSL |
Deployment | Edge + Cloud | Cloud/On-prem | Mostly central |
Indexing & Performance | PB-Scale, Sub-second | Varies | Varies |
Integration | REST, SQL, Common protocols | Varies | Varies |
Performance:
Read more benchmark reports.
- Read the architecture document.
- DeepWiki provides an in-depth look at GreptimeDB:
1. Live Demo
Experience GreptimeDB directly in your browser.
Start instantly with a free cluster.
docker pull greptime/greptimedb
docker run -p 127.0.0.1:4000-4003:4000-4003 \
-v "$(pwd)/greptimedb:/greptimedb_data" \
--name greptime --rm \
greptime/greptimedb:latest standalone start \
--http-addr 0.0.0.0:4000 \
--rpc-bind-addr 0.0.0.0:4001 \
--mysql-addr 0.0.0.0:4002 \
--postgres-addr 0.0.0.0:4003
Dashboard: http://localhost:4000/dashboard
Full Install Guide
Troubleshooting:
- Cannot connect to the database? Ensure that ports
4000
,4001
,4002
, and4003
are not blocked by a firewall or used by other services. - Failed to start? Check the container logs with
docker logs greptime
for further details.
Prerequisites:
- Rust toolchain (nightly)
- Protobuf compiler (>= 3.15)
- C/C++ building essentials, including
gcc
/g++
/autoconf
and glibc library (eg.libc6-dev
on Ubuntu andglibc-devel
on Fedora) - Python toolchain (optional): Required only if using some test scripts.
Build and Run:
make
cargo run -- standalone start
- Kubernetes: GreptimeDB Operator
- Helm Charts: Greptime Helm Charts
- Dashboard: Web UI
- SDKs/Ingester: Go, Java, C++, Erlang, Rust, JS
- Grafana: Official Dashboard
Status: Beta.
GA (v1.0): Targeted for mid 2025.
- Being used in production by early adopters
- Stable, actively maintained, with regular releases (version info)
- Suitable for evaluation and pilot deployments
For production use, we recommend using the latest stable release.
If you find this project useful, a ⭐ would mean a lot to us!
We invite you to engage and contribute!
GreptimeDB is licensed under the Apache License 2.0.
Running GreptimeDB in your organization?
We offer enterprise add-ons, services, training, and consulting.
Contact us for details.
- Read our Contribution Guidelines.
- Explore Internal Concepts and DeepWiki.
- Pick up a good first issue and join the #contributors Slack channel.
Special thanks to all contributors! See AUTHORS.md.
- Uses Apache Arrow™ (memory model)
- Apache Parquet™ (file storage)
- Apache Arrow DataFusion™ (query engine)
- Apache OpenDAL™ (data access abstraction)
- etcd (meta service)