Overview
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:
ποΈ Overview
Provides an overview of integrating GreptimeDB with popular tools for data ingestion, querying, and visualization, including Prometheus, Vector, Grafana, Superset, Metabase, and EMQX.
ποΈ Prometheus
Describes how to use GreptimeDB as a remote storage backend for Prometheus and how to query metrics using Prometheus Query Language (PromQL).
ποΈ Vector
Please refer to the Ingest Data with Vector document for instructions on how to sink data to GreptimeDB using Vector.
ποΈ Kafka
Learn how to ingest observability data from Kafka into GreptimeDB using Vector.
ποΈ Grafana
Steps to configure GreptimeDB as a data source in Grafana using different plugins and data sources, including installation and connection settings.
ποΈ Superset
Guide to configuring GreptimeDB as a database in Apache Superset, including installation steps and connection settings.
ποΈ Metabase
Instructions for configuring GreptimeDB as a data source in Metabase, including installation of the driver plugin and connection settings.
ποΈ EMQX
GreptimeDB can be used as a data system for EMQX.
ποΈ DBeaver
Guide to connecting GreptimeDB to DBeaver using MySQL database drivers, including connection settings and verification steps.
ποΈ Grafana Alloy
Integrate GreptimeDB with Grafana Alloy.
ποΈ Streamlit
Instructions for using GreptimeCloud with Streamlit to build data apps, including creating a SQL connection and running SQL queries.
ποΈ MindsDB
Guide on configuring GreptimeCloud as a data source in MindsDB for machine learning capabilities.