
Hasura GraphQL Engine
Open-source GraphQL engine providing instant, realtime APIs on your data
32.1k stars 3k forks last commit first released Apache-2.0
Actively maintained
Last commit 19 Aug 2026.

Hasura GraphQL Engine provides instant, realtime GraphQL and REST APIs over your data sources by introspecting schemas and exposing a composable, secure API surface. It supports multiple backends and connector SDKs for adding custom business logic, and includes an admin console and migration tooling for managing schema and metadata.
Key Features
- Instant GraphQL APIs generated from database schemas with support for queries, mutations, subscriptions (realtime).
- Fine-grained row- and column-level access control and permission rules.
- Database event triggers and webhooks for serverless workflows and asynchronous processing.
- Data Connectors architecture (V3) enabling Postgres, MongoDB, ClickHouse, MS SQL Server and other sources.
- Connector SDKs for writing custom business logic in TypeScript, Python, and Go.
- Admin console and migration tooling for schema management and metadata versioning.
- Remote schemas and schema stitching to merge custom GraphQL services into a single endpoint.
- Container-friendly deployment with Docker and orchestration support for cloud/Kubernetes environments.
Use Cases
- Rapidly expose an existing database as a secure, realtime GraphQL API for web and mobile apps.
- Build event-driven pipelines by triggering functions or webhooks on database changes.
- Compose data from multiple sources into a unified API for microservices and analytics.
Limitations and Considerations
- Full feature parity depends on the connected data source; some advanced features vary by connector and database capabilities.
- Operational behavior (performance, caching, realtime scalability) is influenced by the underlying datastore and deployment topology.
Hasura is designed to accelerate API development by automating schema-to-API creation and providing production-oriented features for access control, subscriptions, and eventing. It is commonly used to modernize data access, integrate heterogeneous data sources, and power realtime user experiences.
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