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Repos	GreptimeTeam/greptimedb
Views	$\"views\"$
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License	$\"license\"$
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\n \n \n \n $\"GreptimeDB$ \n \n

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Real-Time & Cloud-Native Observability Database
for metrics, logs, and traces

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Delivers sub-second querying at PB scale and exceptional cost efficiency from edge to cloud.
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\n GreptimeCloud |\n User Guide |\n API Docs |\n Roadmap 2025\n

\n\n $\"Version\"$ \n\n\n $\"Releases\"$ \n\n\n $\"Docker$ \n\n\n $\"GitHub$ \n\n\n $\"Codecov\"$ \n\n\n $\"License\"$ \n\n
\n\n $\"Slack\"$ \n\n\n $\"Twitter\"$ \n\n\n $\"LinkedIn\"$ \n\n

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Introduction

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GreptimeDB is an open-source, cloud-native database purpose-built for the unified collection and analysis of observability data (metrics, logs, and traces). Whether you’re operating on the edge, in the cloud, or across hybrid environments, GreptimeDB empowers real-time insights at massive scale — all in one system.

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Features

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Feature	Description
Unified Observability Data	Store metrics, logs, and traces as timestamped, contextual wide events. Query via SQL, PromQL, and streaming.
High Performance & Cost Effective	Written in Rust, with a distributed query engine, rich indexing, and optimized columnar storage, delivering sub-second responses at PB scale.
Cloud-Native Architecture	Designed for Kubernetes, with compute/storage separation, native object storage (AWS S3, Azure Blob, etc.) and seamless cross-cloud access.
Developer-Friendly	Access via SQL/PromQL interfaces, REST API, MySQL/PostgreSQL protocols, and popular ingestion protocols.
Flexible Deployment	Deploy anywhere: edge (including ARM/Android) or cloud, with unified APIs and efficient data sync.

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Learn more in Why GreptimeDB and Observability 2.0 and the Database for It.

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Quick Comparison

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Feature	GreptimeDB	Traditional TSDB	Log Stores
Data Types	Metrics, Logs, Traces	Metrics only	Logs only
Query Language	SQL, PromQL, Streaming	Custom/PromQL	Custom/DSL
Deployment	Edge + Cloud	Cloud/On-prem	Mostly central
Indexing & Performance	PB-Scale, Sub-second	Varies	Varies
Integration	REST, SQL, Common protocols	Varies	Varies

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Performance:

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Read more benchmark reports.

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Architecture

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Read the architecture document.
DeepWiki provides an in-depth look at GreptimeDB:
\n $\"GreptimeDB$

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Try GreptimeDB

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1. Live Demo

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Experience GreptimeDB directly in your browser.

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2. GreptimeCloud

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Start instantly with a free cluster.

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3. Docker (Local Quickstart)

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docker pull greptime/greptimedb

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docker run -p 127.0.0.1:4000-4003:4000-4003 \\\n  -v \"$(pwd)/greptimedb_data:/greptimedb_data\" \\\n  --name greptime --rm \\\n  greptime/greptimedb:latest standalone start \\\n  --http-addr 0.0.0.0:4000 \\\n  --rpc-bind-addr 0.0.0.0:4001 \\\n  --mysql-addr 0.0.0.0:4002 \\\n  --postgres-addr 0.0.0.0:4003

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Dashboard: http://localhost:4000/dashboard
\nFull Install Guide

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Troubleshooting:

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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.

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Getting Started

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Build From Source

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Prerequisites:

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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.

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Build and Run:

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make\ncargo run -- standalone start

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Tools & Extensions

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Kubernetes: GreptimeDB Operator
Helm Charts: Greptime Helm Charts
Dashboard: Web UI
SDKs/Ingester: Go, Java, C++, Erlang, Rust, JS
Grafana: Official Dashboard

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Project Status

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Status: Beta.
\nGA (v1.0): Targeted for mid 2025.
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Being used in production by early adopters
Stable, actively maintained, with regular releases (version info)
Suitable for evaluation and pilot deployments

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For production use, we recommend using the latest stable release.
\n $\"Star$

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If you find this project useful, a ⭐ would mean a lot to us!
\n $\"Known$

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Community

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We invite you to engage and contribute!

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License

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GreptimeDB is licensed under the Apache License 2.0.

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Commercial Support

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Running GreptimeDB in your organization?
\nWe offer enterprise add-ons, services, training, and consulting.
\nContact us for details.

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Contributing

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Read our Contribution Guidelines.
Explore Internal Concepts and DeepWiki.
Pick up a good first issue and join the #contributors Slack channel.

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Acknowledgement

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Special thanks to all contributors! See AUTHORS.md.

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Uses Apache Arrow™ (memory model)
Apache Parquet™ (file storage)
Apache Arrow DataFusion™ (query engine)
Apache OpenDAL™ (data access abstraction)

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