dennis zhuang
e778a72829
* feat(operator): pair calls edges across trace tables and derive virtual-node edges Union the normalized client and server spans of all trace tables before the join, so a client span pairs with a server span stored in a different table. A client span with no matching server span becomes an edge to a virtual node named by span attributes (peer.service / db.name / server.address), with confidence < 1.0 and attributes.connection_type; a window's real pairs win over virtual candidates for the same edge key. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * feat(operator): derive same-row co-declared edges from the built-in vocabulary A table declaring both entity types of a vocabulary pair witnesses the edge on every row carrying both identities: runs_on / contains / part_of for any declaring table (provenance 'attribute'), agent uses model / agent invoked tool only for trace sources (span-structure observations, provenance 'trace'). Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * feat(operator): derive parent_agent-calls-agent edges from span structure Trace tables declaring an agent entity pair each span with its child span across tables (no span-kind filter), keep pairs whose agent identities differ, and aggregate RED metrics per window, anchored on the parent span like the service derivation is anchored on the client. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * feat(frontend): feed co-declared and agent sources into the relationships scan scan_relationships now passes every declaring table (with its trace-ness) to the co-declared branch and the trace tables' agent declarations to the agent-calls derivation. enumerate validates the fixed trace-v1 columns and derives around a malformed trace table instead of failing the whole scan. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * test: cover cross-table pairing, virtual nodes, co-declared and agent edges sqlness exercises the new derivations end to end (including a malformed trace-model table being skipped); the integration authorization test now also pins that a pair split across tables derives no edge when the caller cannot read one side. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * chore: update the relationships module doc for the new branches Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * chore: import shared derivation helpers via crate paths The fmt CI gate rejects module-level 'use super::' imports. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: fold co-declared duplicates, decouple agent calls, verify the trace time index Review findings: the co-declared branch lacked a cross-source DISTINCT, so two tables witnessing the same edge in one window emitted duplicate rows; the agent-calls derivation was gated on a usable service declaration; the trace schema guard accepted a table whose time index is not the column the derivations bucket by. The empty-trace-table test asserted a union invariant with no information and is dropped. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: rename the agent-tool edge to invokes and track current OTel peer attributes The vocabulary's other relation names are present tense; semconv 1.39/1.26 replaced peer.service and db.name with service.peer.name and db.namespace, so the virtual-node candidates now check the current names first and keep the deprecated ones for existing telemetry. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: trust the trace-v1 table option instead of matching the fixed schema The option is only ever stamped by the ingest path, which guarantees the fixed span columns; matching column types here couples the graph to every trace schema evolution (e.g. #8816) for a case that cannot occur. Signed-off-by: Dennis Zhuang <killme2008@gmail.com> --------- Signed-off-by: Dennis Zhuang <killme2008@gmail.com>
One database for metrics, logs, and traces
replacing Prometheus, Loki, and Elasticsearch
The unified OpenTelemetry backend — with SQL + PromQL on object storage.
User Guide | API Docs | Roadmap 2026
stable for production · latest includes pre-releases · nightly is a weekly snapshot of main
- Introduction
- Overview
- 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 50×.
Overview
A quick overview of what GreptimeDB ingests, how it connects to other systems, and what its distributed engine lets you do.
Features
| Feature | Description |
|---|---|
| Observability 2.0 native | Logs, metrics, and traces in one engine with SQL + PromQL. Native OpenTelemetry, Prometheus remote write, and Jaeger. Migrate one signal at a time, or use as a single backend. |
| Elastic compute-storage separation | Scale reads independently with horizontal replicas. Serve high-concurrency workloads from dashboards, alerting, and AI agents — without resharding or data migration. |
| Sub-second on PB–EB-scale data | Columnar engine with fulltext, inverted, and skipping indexes. Written in Rust. Designed for high-concurrency point queries, not just analytical scans. |
| 50× lower cost | Object storage (S3, GCS, Azure Blob) as primary storage, with a tiered cache (memory + local disk) to keep writes and queries fast. |
Perfect for:
- Replacing Prometheus + Loki + Elasticsearch with a single observability backend
- Scaling past Prometheus — high cardinality, long-term storage, no Thanos/Mimir overhead
- AI/agent workloads — store GenAI telemetry (OTel GenAI conventions), and serve high-concurrency reads from SRE/developer agents via horizontal read replicas
- Cutting observability costs with object storage (up to 50× savings on traces, 30% on logs)
- Edge-to-cloud observability with unified APIs on resource-constrained devices
Why Observability 2.0? Three separate databases for metrics, logs, and traces means three storage layers, three query languages, and three sets of dashboards. GreptimeDB stores all three as timestamped wide events in one columnar engine — JOIN across signals in SQL, run one stack instead of three, and ingest AI agent telemetry the same way. Read more: Observability 2.0 and the Database for It.
Learn more in Why GreptimeDB.
How GreptimeDB Compares
| Capability | 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 50× lower storage cost | 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 — 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, autopilot, 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
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 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.