dennis zhuang
09c0b23a23
* fix(meta): actually acquire logical table locks in alter-logical-tables procedure The procedure listed its logical table locks from table_info_values, which is only filled during Prepare, while procedure lock keys are fixed at submission — so the logical locks were never acquired. Today every writer of a logical table's info is serialized by the physical table lock, which hides the problem; a metadata-only alter procedure targeting a single logical table would race it. Resolve the logical table ids at submission, persist them in the procedure state (serde(default): state dumped by older versions keeps the previous behavior), lock physical + logical tables, and re-check the resolved ids against the locked set at Prepare so a table dropped and recreated after submission cannot be mutated without a lock. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * feat: manage semantic table options via ALTER TABLE SET/UNSET CREATE TABLE accepts greptime.semantic.* options, but ALTER TABLE SET routed every option through SetRegionOption, whose closed match rejects them — tables auto-created by ingestion could never receive semantic declarations after the fact. Semantic options are pure metadata markers no region consumes, so they now take a metadata-only alter, following the repartition-hint precedent: - New AlterKind::SetAnnotations/UnsetAnnotations carrying an AnnotationFamily (currently only Semantic), so future marker-style option families reuse the same machinery. The converter classifies a SET/UNSET batch by key prefix and rejects batches that mix annotation keys with regular options. - The procedure reuses the MetadataOnly flow: no region dispatch, table-info update plus cache invalidation only. - Validation lives in the table-meta mutation layer, so it runs at frontend verification and again in the procedure's prepare step under the table lock: SET is strict (known key, value domain, entity columns exist and render as strings); UNSET is lenient inside the namespace so stale keys can be cleaned up. ModifyColumnTypes re-checks columns referenced by entity declarations at the same layer, closing a verify-then-execute race. - Logical metric tables are supported: an annotation alter submits a regular alter-table task locking only the logical table, and the DDL manager's physical-route guard admits it. - create_table_info re-checks semantic value domains for gRPC-built expressions that bypass the SQL parser. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * refactor(table): centralize annotation option classification and validation Address review feedback on the AnnotationFamily abstraction: with only one variant that every consumer immediately destructured, the generality was fake. Make it real and exhaustive instead: - AnnotationFamily gains RepartitionHint: repartition.column.hint is the same kind of marker option (pure metadata, no region consumes it) and previously had a hand-rolled special case in the converter, the metadata-only classifier, and a dedicated AlterKind pair — all deleted, one classification API remains. Per-family logical-table eligibility (allows_logical_tables) replaces the hard-coded Semantic check in the DDL manager guard. - One validation core in the table crate (check_annotation) serves both DDL entry points. CREATE and ALTER previously duplicated the rules; each keeps its existing error variants, status codes and messages via thin adapters over a typed error (ALTER missing column stays 4002 TableColumnNotFound, CREATE stays InvalidArguments). - The batch classifier returns Result instead of swallowing the mixed-batch error: a mixed SET on a logical table now reports the actual problem instead of UnexpectedLogicalRouteTable, and the flow classifiers propagate instead of guessing. The converter also moves its owned payloads instead of cloning them. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * test(meta): cover logical-table annotation alter routing The route-guard branch admitting metadata-only annotation alters on logical tables was only exercised end to end by sqlness. Pin it at the DDL manager level: a semantic SET on a logical table succeeds, updates only the logical table's metadata and dispatches nothing to datanodes; a mixed batch reports its own error instead of the route guard's; the repartition hint stays rejected on logical routes. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix(table): keep entity guard on ADD COLUMN and report missing columns first Review follow-ups: the old verify_alter loop scanned the post-alter schema, so it also caught DROP COLUMN followed by re-adding the declared column with a non-string type — the mutation-layer move only kept the MODIFY path. Guard add_columns the same way (this also covers ingestion auto-alter). And run the MODIFY drift check after the existence lookup, so altering a dropped-but-still-declared column reports ColumnNotExists (4002) like every other MODIFY on a missing column. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * style(grpc-expr): drop a test comment restating the classifier doc Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * refactor(table): rename annotation validation helpers per review check_annotation* validated and normalized; align the names with the validate_and_normalize_* convention nearby, and spell out AnnotationContext (Cx is not used in this repo). Signed-off-by: Dennis Zhuang <killme2008@gmail.com> --------- Signed-off-by: Dennis Zhuang <killme2008@gmail.com>
Metrics, logs, and traces.
One engine, on your infrastructure.
A columnar database for metrics, logs, and traces on object storage. Apache-2.0 licensed core.
User Guide | API Docs | Roadmap 2026
stable for production · canary includes pre-releases · nightly is a weekly snapshot of main
- Introduction
- Why You Might Use It
- Overview
- What's Supported
- Compatibility and Migration
- Limitations and Edition Boundary
- 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. Metrics, logs, and traces run on one columnar engine over object storage and share one table model: tags, timestamp, and fields. When signals carry common identifiers such as service, host, or trace ID, you can correlate them in SQL without moving data between databases.
Ingest through OpenTelemetry, Prometheus Remote Write, Loki Push, or Elasticsearch Bulk. Use SQL across observability data and PromQL for metrics. Migrate ingestion one signal at a time without rebuilding your collectors.
Why You Might Use It
- You run Prometheus plus Loki or Elasticsearch and want one backend instead of three
- You have outgrown Prometheus on cardinality or retention and don't want the Thanos/Mimir operational surface
- You need long retention on object storage without a separate analytics stack
- You want to query telemetry with SQL, not only a domain query language
- You are storing GenAI or agent telemetry (OTel GenAI conventions) alongside infrastructure signals
- You need the same engine and semantics on resource-constrained devices
Learn more in Why GreptimeDB.
Overview
A quick overview of what GreptimeDB ingests, how it connects to other systems, and what its distributed engine lets you do.
What's Supported
| Ingest | OpenTelemetry (OTLP), Prometheus Remote Write, Loki Push, Elasticsearch Bulk, InfluxDB line protocol, gRPC |
| Query | SQL, PromQL, Jaeger-compatible trace queries, MySQL and PostgreSQL wire protocols |
| Storage | S3, GCS, Azure Blob and S3-compatible endpoints as primary storage, with memory and local-disk caches |
| Built in | Retention policies, downsampling, continuous aggregation, explicit table partitioning, and inverted / skipping / fulltext indexes |
Compute and storage are disaggregated: object storage holds the data, while memory and local-disk caches keep recent and frequently queried data close to compute.
Compatibility and Migration
Compatibility is per protocol, and query-side coverage is narrower than ingestion.
| Compatible | Not compatible | |
|---|---|---|
| Prometheus | Remote Write ingestion; PromQL queries | Gaps are listed in PromQL compatibility |
| Loki | Push ingestion; dual-write through Grafana Alloy makes the cutover gradual | LogQL and the rest of the Loki query API |
| Elasticsearch | _bulk ingestion in the open-source core; QueryDSL partially, in Enterprise |
Most other Elasticsearch APIs |
Benchmarks:
Limitations and Edition Boundary
Cluster deployment, object storage, the Flow engine, and every ingestion protocol listed above are in the Apache-2.0 build. Repartitioning, region migration, and index creation are manual operations there.
Read replicas, workload isolation, and automated repartitioning are GreptimeDB Enterprise features, along with enterprise security and governance. The Enterprise overview has the current list, and pricing has the edition comparison.
Architecture
GreptimeDB can run in two modes:
- Standalone — single binary for development and small deployments.
- Distributed — four components, each independently scalable:
- Frontend — protocol entry (OTel, Prometheus, MySQL/PostgreSQL, gRPC, ingestion APIs for Elasticsearch/InfluxDB/Loki) and the distributed query engine. Stateless, scales horizontally.
- Datanode — region engine with WAL, memtable, SST, cache, compaction, and indexes. Persists data to object storage. Elastic.
- Metasrv — metadata, routing, repartitioning, and security. Backed by a pluggable KV layer (etcd or RDS).
- Flownode (optional) — continuous flow computation (streaming and materialized views).
For deeper coverage, see the architecture doc or DeepWiki.
Try GreptimeDB
For AI agents — paste this prompt into your agent:
Read https://docs.greptime.com/SKILL.md and follow the instructions
to deploy, configure, ingest, and query 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 \
--grpc-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, pinned by
rust-toolchain.toml - Protobuf compiler (>= 3.15)
- C/C++ building essentials:
gcc/g++/autoconfand the glibc dev package (libc6-devon Ubuntu,glibc-develon Fedora) - Python toolchain (optional, only for some test scripts)
Build and run:
make # build greptime binary
cargo run -- standalone start # start in standalone mode
Common dev commands:
make fmt # format Rust code
make clippy # lint (fails on warnings)
make test # unit + integration tests (uses cargo-nextest)
make sqlness-test # SQL regression tests
See the Contribution Guidelines for the full developer workflow.
Tools & Extensions
- Kubernetes: GreptimeDB Operator
- Helm Charts: Greptime Helm Charts
- Dashboard: Web UI
- gRPC Ingester: Go, Java, C++, Erlang, Rust, .NET, TypeScript
- Grafana Data Source: GreptimeDB Grafana data source plugin
- Grafana Dashboard: Official Dashboard for monitoring
Project Status
GreptimeDB is generally available, with stable APIs and regular releases. It runs in production at scale — OceanBase Cloud operates 80+ GreptimeDB clusters managing 300 TB of logs, cutting log storage cost by 60%+ after migrating from Grafana Loki. See more in case studies.
Read the v1.0 highlights and 2026 roadmap, or browse the version reference.
If GreptimeDB is useful to you, please star the repo.
Community
We invite you to engage and contribute!
License
GreptimeDB is an open-core project. Its core is licensed under the Apache License 2.0.
A small set of peripheral, enterprise-only features are gated behind the
enterprise Cargo feature (not built by default) and are governed by the
separate GreptimeDB Enterprise License. Source files under
that license carry an explicit Enterprise License header.
Commercial Support
Scaling observability on your infrastructure? GreptimeDB Enterprise adds the operational, security, and support layer for production deployments. 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 AUTHOR.md.
- Uses Apache Arrow™ (memory model)
- Apache Parquet™ (file storage)
- Apache DataFusion™ (query engine)
- Apache OpenDAL™ (data access abstraction)
All trademarks, logos, and brand names referenced in this README and in the Overview diagram are the property of their respective owners. Their use is for identification purposes only and does not imply endorsement or affiliation.