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* fix/fast-path-for-single-region-bulk-insert: ### Commit Summary - **Refactor `try_decode` Method**: Updated the `try_decode` method in `FlightDecoder` to accept a reference to `FlightData` instead of consuming it. This change affects multiple files including `database.rs`, `region.rs`, `flight.rs`, `bulk_insert.rs`, `stream.rs`, and `region_request.rs`. - **Optimize Bulk Insert Handling**: Added a fast path for handling bulk inserts when only one region is involved in `bulk_insert.rs`. * fix/fast-path-for-single-region-bulk-insert: Improve `FlightDecoder` usage in tests - Updated `try_decode` method calls in `flight.rs` to remove unnecessary references for `d1`, `d2`, and `d3`. - Ensured consistency in handling `FlightMessage` variants within test cases. * fix/fast-path-for-single-region-bulk-insert: **Enhancement: Skip Empty Regions in Bulk Insert** - Updated `bulk_insert.rs` to improve efficiency by skipping regions without data during the bulk insert process. This change ensures that regions with a `true_count` of zero are not processed, optimizing resource usage and performance. * fix/fast-path-for-single-region-bulk-insert: ### Commit Summary - **Refactor `RegionMask` Handling**: - Introduced `RegionMask` struct to encapsulate boolean array and selected rows count. - Updated methods to use `RegionMask` instead of `BooleanArray` for region selection. - Affected files: `bulk_insert.rs`, `multi_dim.rs`, `partition.rs`, `splitter.rs`. - **Optimize Region Selection**: - Removed unnecessary checks for empty regions in `bulk_insert.rs`. - Improved logic for handling default regions in `multi_dim.rs`. - **Update Tests**: - Modified test cases to accommodate `RegionMask` changes. - Affected files: `multi_dim.rs`, `splitter.rs`. * fix/fast-path-for-single-region-bulk-insert: **Enhancements to MultiDimPartitionRule Logic and Tests** - **`multi_dim.rs`**: Improved the logic for selecting rows in `MultiDimPartitionRule` by optimizing the selection process when only one region is present. - **Tests**: Added new test cases to verify the behavior of default regions with unselected rows, existing default regions, and scenarios where all rows are selected. These tests ensure robust handling of partition rules and validate the correct assignment of rows to regions.
Real-Time & Cloud-Native Observability Database
for metrics, logs, and traces
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
Introduction
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.
Features
| 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.
Quick Comparison
| 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.
Architecture
- Read the architecture document.
- DeepWiki provides an in-depth look at GreptimeDB:
Try GreptimeDB
1. Live Demo
Experience GreptimeDB directly in your browser.
2. GreptimeCloud
Start instantly with a free cluster.
3. Docker (Local Quickstart)
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, and4003are not blocked by a firewall or used by other services. - Failed to start? Check the container logs with
docker logs greptimefor further details.
Getting Started
Build From Source
Prerequisites:
- Rust toolchain (nightly)
- Protobuf compiler (>= 3.15)
- C/C++ building essentials, including
gcc/g++/autoconfand glibc library (eg.libc6-devon Ubuntu andglibc-develon Fedora) - Python toolchain (optional): Required only if using some test scripts.
Build and Run:
make
cargo run -- standalone start
Tools & Extensions
- Kubernetes: GreptimeDB Operator
- Helm Charts: Greptime Helm Charts
- Dashboard: Web UI
- SDKs/Ingester: Go, Java, C++, Erlang, Rust, JS
- Grafana: Official Dashboard
Project Status
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!
Community
We invite you to engage and contribute!
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 Arrow DataFusion™ (query engine)
- Apache OpenDAL™ (data access abstraction)
- etcd (meta service)