Integrations
CloudQuery’s modular architecture allows you to connect hundreds of data sources to any destination of your choice. This section covers all available integrations and how to work with them. Learn more about integration architecture and how syncs work.
Source Integrations
Source integrations extract data from cloud providers, databases, SaaS applications, and other APIs. They handle authentication, data extraction, and schema definition.
Destination Integrations
Destination integrations write data to databases, data warehouses, message queues, and storage systems. They handle schema migration and data persistence.
Browse Destination Integrations →
Creating Custom Integrations
Learn how to build your own source or destination integrations using CloudQuery’s SDKs. After development, you can publish integrations to the hub.
Integration Architecture
CloudQuery integrations communicate over gRPC and are language-agnostic. They can be implemented in Go, Python, Java, JavaScript, and other languages that support gRPC and Apache Arrow.
Key Features
- Modular Design: Mix and match any source with any destination
- Language Agnostic: Write integrations in your preferred language
- High Performance: Built on Apache Arrow for fast data processing
- Extensible: Create custom integrations for your specific needs
- Community Driven: Both official and community-maintained integrations
Getting Started
- Choose a Source: Browse our source integrations to find the data you need
- Select a Destination: Pick from our destination integrations for your data warehouse
- Configure: Use our configuration guide to set up your sync
- Run: Execute your first sync with
cloudquery sync
Popular Combinations
- AWS → PostgreSQL: Cloud infrastructure data to relational database
- GitHub → ClickHouse: Repository data to analytical database
- GCP → BigQuery: Google Cloud resources to BigQuery data warehouse
- Azure → Snowflake: Microsoft Cloud data to Snowflake data platform