Integrations

GreptimeDB can be seamlessly integrated with popular tools for data ingestion, querying, and visualization. The subsequent sections offer comprehensive guidance on integrating GreptimeDB with the following tools:

📄️ Overview

Overview of integrating GreptimeDB with popular tools for data ingestion, querying, visualization, business intelligence, and AI.

📄️ Prometheus

Describes how to use GreptimeDB as a remote storage backend for Prometheus and how to query metrics using Prometheus Query Language (PromQL).

📄️ Vector

Guide on using Vector to sink data to GreptimeDB.

📄️ Kafka

Learn how to ingest observability data from Kafka into GreptimeDB using Vector.

📄️ Telegraf

Guide on using Telegraf to send data to GreptimeDB

📄️ Grafana

Steps to configure GreptimeDB as a data source in Grafana using different plugins and data sources, including installation and connection settings.

📄️ Perses

Configure GreptimeDB as a datasource in Perses using the GreptimeDB and Prometheus plugins to query metrics, logs, and traces.

📄️ Superset

Guide to configuring GreptimeDB as a database in Apache Superset, including installation steps and connection settings.

📄️ Metabase

Instructions for configuring GreptimeDB as a data source in Metabase, including installation of the driver plugin and connection settings.

📄️ EMQX

Use GreptimeDB as a data system for EMQX to store MQTT messages.

📄️ DBeaver

Guide to connecting GreptimeDB to DBeaver using MySQL database drivers, including connection settings and verification steps.

📄️ Grafana Alloy

Integrate GreptimeDB with Grafana Alloy.

📄️ Streamlit

Instructions for using GreptimeDB with Streamlit to build data apps, including creating a SQL connection and running SQL queries.

📄️ MindsDB

Guide on configuring GreptimeDB as a data source in MindsDB for machine learning capabilities.

📄️ Fluent Bit

Integrate GreptimeDB with Fluent Bit.

📄️ Coroot

Integrate GreptimeDB with Coroot.

📄️ Model Context Protocol (MCP)

Learn how to integrate GreptimeDB with Model Context Protocol (MCP) for AI assistants to explore and analyze your metrics, logs, and traces.