GreptimeDB: Cloud-Native Observability Database for Metrics, Logs, and Traces

Summary

GreptimeDB is an open-source, cloud-native database designed for unified observability, handling metrics, logs, and traces. Built in Rust, it offers real-time querying at PB scale with exceptional cost efficiency, supporting SQL and PromQL. It's ideal for large-scale observability platforms and IoT/edge computing environments.

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Introduction

GreptimeDB is an open-source, cloud-native database that unifies metrics, logs, and traces, enabling real-time observability at any scale, across edge, cloud, and hybrid environments. It delivers sub-second querying at PB scale and exceptional cost efficiency.

Installation

To get started with GreptimeDB, the quickest way is using Docker.

First, pull the latest image:

docker pull greptime/greptimedb

Then, run the container, exposing the necessary ports:

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

After running, you can access the dashboard at http://localhost:4000/dashboard. For more detailed instructions, refer to the full Install Guide.

Examples

GreptimeDB provides various resources to help you get started and explore its capabilities.

Quickstart: Follow the Quickstart guide to set up your first instance and ingest data.
User Guide: Dive deeper into the features and usage with the comprehensive User Guide.
Demo Scenes: Explore practical use cases and examples in the GreptimeTeam/demo-scene repository.

Why Use GreptimeDB

GreptimeDB stands out as a powerful solution for modern observability needs due to several key features:

All-in-One Observability: It provides a unified platform for metrics, logs, and traces, natively supporting OpenTelemetry and allowing queries via SQL, PromQL, and Flow. This simplifies your observability stack, potentially replacing multiple tools like Prometheus, Loki, and Tempo.
High Performance: Built in Rust, GreptimeDB offers rich indexing capabilities (inverted, fulltext, skipping, vector) to deliver sub-second responses even at petabyte scale. It excels in handling large-scale metrics with high cardinality.
Cost Efficiency: With its compute-storage separation and native object storage support (S3, Azure Blob, etc.), GreptimeDB achieves significantly lower operational and storage costs.
Cloud-Native & Scalable: Designed for Kubernetes, it offers unlimited cross-cloud scaling and can handle hundreds of thousands of concurrent requests, making it suitable for demanding production environments.
Developer-Friendly: It provides familiar interfaces like SQL/PromQL, a built-in web dashboard, REST API, MySQL/PostgreSQL protocol compatibility, and native OpenTelemetry support, making it easy for developers to integrate and use.
Flexible Deployment: GreptimeDB can be deployed anywhere, from ARM-based edge devices (including Android) to cloud environments, with unified APIs and efficient data synchronization.