DdlManager (#7548)
* feat: add repartition procedure factory support to DdlManager - Introduce RepartitionProcedureFactory trait for creating and registering repartition procedures - Implement DefaultRepartitionProcedureFactory for metasrv with full support - Implement StandaloneRepartitionProcedureFactory for standalone (unsupported) - Add procedure loader registration for RepartitionProcedure and RepartitionGroupProcedure - Add helper methods to TableMetadataAllocator for allocator access - Add error types for repartition procedure operations - Update DdlManager to accept and use RepartitionProcedureFactoryRef Signed-off-by: WenyXu <wenymedia@gmail.com> * feat: integrate repartition procedure into DdlManager - Add submit_repartition_task() to handle repartition from alter table - Route Repartition operations in submit_alter_table_task() to repartition factory - Refactor: rename submit_procedure() to execute_procedure_and_wait() - Make all DDL operations wait for completion by default - Add submit_procedure() for fire-and-forget submissions - Add CreateRepartitionProcedure error type - Add placeholder Repartition handling in grpc-expr (unsupported) - Update greptime-proto dependency Signed-off-by: WenyXu <wenymedia@gmail.com> * feat: implement ALTER TABLE REPARTITION procedure submission Signed-off-by: WenyXu <wenymedia@gmail.com> * refactor(repartition): handle central region in apply staging manifest - Introduce ApplyStagingManifestInstructions struct to organize instructions - Add special handling for central region when applying staging manifests - Transition state from UpdateMetadata to RepartitionEnd after applying staging manifests - Remove next_state() method in RepartitionStart and inline state transitions - Improve logging and expression serialization in DDL statement executor - Move repartition tests from standalone to distributed test suite Signed-off-by: WenyXu <wenymedia@gmail.com> * chore: apply suggestions from CR Signed-off-by: WenyXu <wenymedia@gmail.com> * chore: update proto Signed-off-by: WenyXu <wenymedia@gmail.com> --------- Signed-off-by: WenyXu <wenymedia@gmail.com>
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 that unifies metrics, logs, and traces, enabling real-time observability at any scale — across edge, cloud, and hybrid environments.
Features
| Feature | Description |
|---|---|
| All-in-One Observability | OpenTelemetry-native platform unifying metrics, logs, and traces. Query via SQL, PromQL, and Flow. |
| High Performance | Written in Rust with rich indexing (inverted, fulltext, skipping, vector), delivering sub-second responses at PB scale. |
| Cost Efficiency | 50x lower operational and storage costs with compute-storage separation and native object storage (S3, Azure Blob, etc.). |
| Cloud-Native & Scalable | Purpose-built for Kubernetes with unlimited cross-cloud scaling, handling hundreds of thousands of concurrent requests. |
| Developer-Friendly | SQL/PromQL interfaces, built-in web dashboard, REST API, MySQL/PostgreSQL protocol compatibility, and native OpenTelemetry support. |
| Flexible Deployment | Deploy anywhere from ARM-based edge devices (including Android) to cloud, with unified APIs and efficient data sync. |
✅ Perfect for:
- Unified observability stack replacing Prometheus + Loki + Tempo
- Large-scale metrics with high cardinality (millions to billions of time series)
- Large-scale observability platform requiring cost efficiency and scalability
- IoT and edge computing with resource and bandwidth constraints
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 | Custom/PromQL | Custom/DSL |
| Deployment | Edge + Cloud | Cloud/On-prem | Mostly central |
| Indexing & Performance | PB-Scale, Sub-second | Varies | Varies |
| Integration | REST API, SQL, Common protocols | Varies | Varies |
Performance:
Read 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
docker pull greptime/greptimedb
docker run -p 127.0.0.1:4000-4003:4000-4003 \
-v "$(pwd)/greptimedb_data:/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
Read more in the 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
- gRPC Ingester: Go, Java, C++, Erlang, Rust
- Grafana Data Source: GreptimeDB Grafana data source plugin
- Grafana Dashboard: Official Dashboard for monitoring
Project Status
Status: Beta — marching toward v1.0 GA! GA (v1.0): January 10, 2026
- Deployed in production by open-source projects and commercial users
- Stable, actively maintained, with regular releases (version info)
- Suitable for evaluation and pilot deployments
GreptimeDB v1.0 represents a major milestone toward maturity — marking stable APIs, production readiness, and proven performance.
Roadmap: Beta1 (Nov 10) → Beta2 (Nov 24) → RC1 (Dec 8) → GA (Jan 10, 2026), please read v1.0 highlights and release plan for details.
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 DataFusion™ (query engine)
- Apache OpenDAL™ (data access abstraction)
