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* fix unit tests * fix: sqlness * fix/default-time-window: ## Add Helper Functions and Enhance Compaction Tests - **Refactor Compaction Logic**: Introduced helper functions `flush` and `compact` in `compaction_test.rs` to streamline compaction operations. - **Enhance Compaction Tests**: Added a new test `test_infer_compaction_time_window` in `compaction_test.rs` to verify compaction time window inference. - **Testing Improvements**: Added `#[cfg(test)]` attribute to `new_multi_partitions` in `time_partition.rs` to ensure it's only included in test builds. * fix/default-time-window: - **Refactor `TimePartition` Struct**: Removed unnecessary comments regarding `time_range` in `time_partition.rs`. - **Enhance `TimePartitions` Functionality**: Added a method `part_duration_or_default` to provide a default partition duration in `time_partition.rs`. - **Update SQL Test Cases**: Modified SQL operations and expected results in `scan_big_varchar.result` and `scan_big_varchar.sql` to reflect changes in data manipulation logic. * fix/default-time-window: ### Update Time Partition Default Duration - **Refactor Default Duration**: Introduced `INITIAL_TIME_WINDOW` constant to define the default time window duration as `Duration::from_days(1)`. This change replaces multiple instances of the hardcoded default duration across the `time_partition.rs` file. - **Files Affected**: `time_partition.rs` * fix/default-time-window: ## Update Partition Duration Handling - **`time_partition.rs`**: Refactored `part_duration` to be non-optional, removing `Option` wrapper. Updated logic to use `unwrap_or` with `INITIAL_TIME_WINDOW` where necessary. Adjusted related methods and tests to accommodate this change. - **`version.rs` (memtable and region)**: Updated handling of `part_duration` to align with changes in `time_partition.rs`, ensuring consistent use of non-optional `Duration`. * fix/default-time-window: ### Improve Error Context in `time_partition.rs` - Enhanced error context message in `time_partition.rs` to provide clearer information on partition time range issues, including bucket size details. Signed-off-by: Lei, HUANG <lhuang@greptime.com> --------- Signed-off-by: Lei, HUANG <lhuang@greptime.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 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_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 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)