Greptimedb

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:

• GreptimeDB tops JSONBench's billion-record cold run test
• TSBS Benchmark
• More benchmark reports

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 \
  --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, and 4003 are not blocked by a firewall or used by other services.
• Failed to start? Check the container logs with docker logs greptime for further details.

Getting Started

• Quickstart
• User Guide
• Demo Scenes
• FAQ

Build From Source

Prerequisites:

• Rust toolchain (nightly)
• Protobuf compiler (>= 3.15)
• C/C++ building essentials, including gcc/g++/autoconf and glibc library (eg. libc6-dev on Ubuntu and glibc-devel on 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: v1.0 GA — generally available and production-ready! 🎉

• Deployed in production handling billions of data points daily
• Stable APIs, actively maintained, with regular releases (version info)

GreptimeDB v1.0 marks a major milestone — stable APIs, production readiness, and proven performance at scale.

Learn more: v1.0 highlights and 2026 roadmap.

For production use, we recommend v1.0 or later.

If you find this project useful, a ⭐ would mean a lot to us!

Community

We invite you to engage and contribute!

• Slack
• Discussions
• Official Website
• Blog
• LinkedIn
• X (Twitter)
• YouTube

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)