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* feat: ordered builder wip * feat: impl RegionScanner for SeqScan * feat: implement scan_partition and build_stream * chore: return SeqScan as RegionScanner * fix: group parts * feat: split parts * chore: reader metrics * chore: metrics * chore: remove unused codes * chore: support holding a group of ranges in ScanPart * feat: group ScanParts to ScanParts * feat: impl SeqScanner again * chore: observe build cost in ScannerMetrics * chore: fix compiler warnings * style: fix clippy * docs: update config docs * chore: forward DisplayAs to scanner * test: update sqlness tests * chore: update debug fmt * chore: custom debug for timestamp fix test compiling issue with common-macro when running cargo nextest -p common-time * chore: update debug format * feat: update fmt for scan part * chore: fix warning * fix: sanitize parallelism * feat: split parts * test: fix config api test * feat: update logs * chore: Revert "chore: remove unused codes" This reverts commit b548b30a01eeded59b1a0a8d89f9293ca63afc41. * chore: Revert "docs: update config docs" This reverts commit a7997e78d6ddcf635560574de8c1948c495bdd12. * feat: each partition scan files in parallel * test: fix config api test * docs: fix typo * chore: address comments, simplify tests * feat: global semaphore * feat: always spawn task * chore: simplify default explain output format * handle output partiton number is 0 Signed-off-by: Ruihang Xia <waynestxia@gmail.com> * fix typo Signed-off-by: Ruihang Xia <waynestxia@gmail.com> --------- Signed-off-by: Ruihang Xia <waynestxia@gmail.com> Co-authored-by: Ruihang Xia <waynestxia@gmail.com>
Cloud-scale, Fast and Efficient Time Series Database
Introduction
GreptimeDB is an open-source time-series database focusing on efficiency, scalability, and analytical capabilities. Designed to work on infrastructure of the cloud era, GreptimeDB benefits users with its elasticity and commodity storage, offering a fast and cost-effective alternative to InfluxDB and a long-term storage for Prometheus.
Why GreptimeDB
Our core developers have been building time-series data platforms for years. Based on our best-practices, GreptimeDB is born to give you:
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Easy horizontal scaling
Seamless scalability from a standalone binary at edge to a robust, highly available distributed cluster in cloud, with a transparent experience for both developers and administrators.
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Analyzing time-series data
Query your time-series data with SQL and PromQL. Use Python scripts to facilitate complex analytical tasks.
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Cloud-native distributed database
Fully open-source distributed cluster architecture that harnesses the power of cloud-native elastic computing resources.
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Performance and Cost-effective
Flexible indexing capabilities and distributed, parallel-processing query engine, tackling high cardinality issues down. Optimized columnar layout for handling time-series data; compacted, compressed, and stored on various storage backends, particularly cloud object storage with 50x cost efficiency.
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Compatible with InfluxDB, Prometheus and more protocols
Widely adopted database protocols and APIs, including MySQL, PostgreSQL, and Prometheus Remote Storage, etc. Read more.
Try GreptimeDB
1. GreptimePlay
Try out the features of GreptimeDB right from your browser.
2. GreptimeCloud
Start instantly with a free cluster.
3. Docker Image
To install GreptimeDB locally, the recommended way is via Docker:
docker pull greptime/greptimedb
Start a GreptimeDB container with:
docker run --rm --name greptime --net=host greptime/greptimedb standalone start
Read more about Installation on docs.
Getting Started
Build
Check the prerequisite:
- Rust toolchain (nightly)
- Protobuf compiler (>= 3.15)
- Python toolchain (optional): Required only if built with PyO3 backend. More detail for compiling with PyO3 can be found in its documentation.
Build GreptimeDB binary:
make
Run a standalone server:
cargo run -- standalone start
Extension
Dashboard
SDK
- GreptimeDB Go Ingester
- GreptimeDB Java Ingester
- GreptimeDB C++ Ingester
- GreptimeDB Erlang Ingester
- GreptimeDB Rust Ingester
- GreptimeDB JavaScript Ingester
Grafana Dashboard
Our official Grafana dashboard is available at grafana directory.
Project Status
The current version has not yet reached General Availability version standards. In line with our Greptime 2024 Roadmap, we plan to achieve a production-level version with the update to v1.0 in August. [Join Force]
Community
Our core team is thrilled to see you participate in any ways you like. When you are stuck, try to ask for help by filling an issue with a detailed description of what you were trying to do and what went wrong. If you have any questions or if you would like to get involved in our community, please check out:
- GreptimeDB Community on Slack
- GreptimeDB GitHub Discussions forum
- Greptime official website
In addition, you may:
License
GreptimeDB uses the Apache License 2.0 to strike a balance between open contributions and allowing you to use the software however you want.
Contributing
Please refer to contribution guidelines and internal concepts docs for more information.
Acknowledgement
- GreptimeDB uses Apache Arrow™ as the memory model and Apache Parquet™ as the persistent file format.
- GreptimeDB's query engine is powered by Apache Arrow DataFusion™.
- Apache OpenDAL™ gives GreptimeDB a very general and elegant data access abstraction layer.
- GreptimeDB's meta service is based on etcd.
- GreptimeDB uses RustPython for experimental embedded python scripting.