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* perf: optimize Prometheus label name decoding with byte-level validation Add `decode_label_name` and `validate_label_name` to skip redundant UTF-8 validation for Prometheus label names, which are guaranteed ASCII (`[a-zA-Z_][a-zA-Z0-9_]*`). Rename `validate_bytes` to `validate_utf8` for clarity and add benchmarks for label name validation and UTF-8 validation (std vs simdutf8). Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * perf(servers): optimize validate_label_name with lookup table and loop unrolling Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * perf/decode-prom-2: - **Refactor UTF-8 Validation and Label Decoding**: - Removed `validate_utf8` method and integrated label name validation directly in `decode_label_name` in `http.rs`. - Updated `decode_label_name` to always enforce Prometheus label name validation across all modes. - Adjusted test cases in `http.rs` to reflect the new validation logic. - **Enhance Label Validation in `prom_row_builder.rs`**: - Replaced UTF-8 validation with direct label name validation using `validate_label_name`. - Updated `decode_label_name` usage to return `&str` and adjusted related logic. Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * perf/decode-prom-2: **Refactor `TableBuilder` to Use `RawBytes` for Column Indexes** - Updated `TableBuilder` in `prom_row_builder.rs` to use `RawBytes` instead of `Vec<u8>` for `col_indexes`. - Modified `with_capacity` method to directly insert `RawBytes` for timestamp and value columns. - Adjusted schema handling to use `to_owned` for `tag_name` and directly insert `raw_tag_name` into `col_indexes`. Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * perf/decode-prom-2: ### Commit Message Refactor `PromWriteRequest` Method and Enhance Data Handling - **Refactor Method**: Renamed the `merge` method to `decode` in `PromWriteRequest` to better reflect its functionality. Updated references in `prom_decode.rs`, `prom_store.rs`, and `prom_row_builder.rs`. - **Enhance Data Handling**: Introduced `raw_data` field in `PromWriteRequest` to store a clone of the buffer for potential future use. Updated the `clear` method to reset `raw_data`. Files affected: `prom_decode.rs`, `prom_store.rs`, `prom_row_builder.rs`, `proto.rs`. Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * perf/decode-prom-2: **Commit Summary:** - **Enhancement in `prom_row_builder.rs`:** - Added a new field `raw_data` of type `Bytes` to `TablesBuilder`. - Implemented `set_raw_data` method to update `raw_data`. - Modified `clear` method to reset `raw_data`. - **Refactor in `proto.rs`:** - Removed `raw_data` field from `PromWriteRequest`. - Updated `decode_and_process` method to use `set_raw_data` from `TablesBuilder` for handling raw data. Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * chore: remove duplicated validation Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * perf/decode-prom-2: ### Commit Message Refactor `TablesBuilder` and `TableBuilder` to Use Lifetime Annotations - Updated `prom_store.rs`: - Modified `PROM_WRITE_REQUEST_POOL` and `decode_remote_write_request` to use lifetime annotations for `PromWriteRequest` and `TablesBuilder`. - Updated `prom_row_builder.rs`: - Refactored `TablesBuilder` and `TableBuilder` structs to include lifetime annotations. - Adjusted methods in `TablesBuilder` and `TableBuilder` to accommodate lifetime changes. - Updated `proto.rs`: - Added lifetime annotations to `PromWriteRequest` and its methods. - Modified `add_to_table_data` to use lifetime annotations for `TablesBuilder`. Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> * chore: fmt Signed-off-by: Lei, HUANG <mrsatangel@gmail.com> --------- Signed-off-by: Lei, HUANG <mrsatangel@gmail.com>
One database for metrics, logs, and traces
replacing Prometheus, Loki, and Elasticsearch
The unified OpenTelemetry backend — with SQL + PromQL on object storage.
- Introduction
- ⭐ Key Features
- How GreptimeDB Compares
- Architecture
- Try GreptimeDB
- Getting Started
- Build From Source
- Tools & Extensions
- Project Status
- Community
- License
- Commercial Support
- Contributing
- Acknowledgement
Introduction
GreptimeDB is an open-source observability database built for Observability 2.0 — treating metrics, logs, and traces as one unified data model (wide events) instead of three separate pillars.
Use it as the single OpenTelemetry backend — replacing Prometheus, Loki, and Elasticsearch with one database built on object storage. Query with SQL and PromQL, scale without pain, cut costs up to 50x.
Features
| Feature | Description |
|---|---|
| Drop-in replacement | PromQL, Prometheus remote write, Jaeger, and OpenTelemetry native. Use as your single backend for all three signals, or migrate one at a time. |
| 50x lower cost | Object storage (S3, GCS, Azure Blob etc.) as primary storage. Compute-storage separation scales without pain. |
| SQL + PromQL | Monitor with PromQL, analyze with SQL. One database replaces Prometheus + your data warehouse. |
| Sub-second at PB-EB scale | Columnar engine with fulltext, inverted, and skipping indexes. Written in Rust. |
✅ Perfect for:
- Replacing Prometheus + Loki + Elasticsearch with one database
- Scaling past Prometheus — high cardinality, long-term storage, no Thanos/Mimir overhead
- Cutting observability costs with object storage (up to 50x savings on traces, 30% on logs)
- AI/LLM observability — store and analyze high-volume conversation data, agent traces, and token metrics via OpenTelemetry GenAI conventions
- Edge-to-cloud observability with unified APIs on resource-constrained devices
Why Observability 2.0? The three-pillar model (separate databases for metrics, logs, traces) creates data silos and operational complexity. GreptimeDB treats all observability data as timestamped wide events in a single columnar engine — enabling cross-signal SQL JOINs, eliminating redundant infrastructure, and naturally supporting emerging workloads like AI agent observability. Read more: Observability 2.0 and the Database for It.
Learn more in Why GreptimeDB.
How GreptimeDB Compares
| Feature | GreptimeDB | Prometheus / Thanos / Mimir | Grafana Loki | Elasticsearch |
|---|---|---|---|---|
| Data types | Metrics, logs, traces | Metrics only | Logs only | Logs, traces |
| Query language | SQL + PromQL | PromQL | LogQL | Query DSL |
| Storage | Native object storage (S3, etc.) | Local disk + object storage (Thanos/Mimir) | Object storage (chunks) | Local disk |
| Scaling | Compute-storage separation, stateless nodes | Federation / Thanos / Mimir — multi-component, ops heavy | Stateless + object storage | Shard-based, ops heavy |
| Cost efficiency | Up to 50x lower storage | High at scale | Moderate | High (inverted index overhead) |
| OpenTelemetry | Native (metrics + logs + traces) | Partial (metrics only) | Partial (logs only) | Via instrumentation |
Benchmarks:
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, .NET
- Grafana Data Source: GreptimeDB Grafana data source plugin
- Grafana Dashboard: Official Dashboard for monitoring
Project Status
Status: RC — marching toward v1.0 GA! GA (v1.0): March 2026
- Deployed in production handling billions of data points daily
- Stable APIs, actively maintained, with regular releases (version info)
GreptimeDB v1.0 represents a major milestone toward maturity — marking stable APIs, production readiness, and proven performance.
Roadmap: v1.0 highlights and release plan and 2026 roadmap.
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)