Hasura is a universal data access layer and a metadata-driven API platform designed to radically accelerate the creation, deployment, and management of high-quality APIs on top of existing data.

The main features of this tool include:

• Instant API Generation: Hasura allows developers to connect a database instance and automatically generate a GraphQL API based on the existing schema, significantly reducing manual backend effort.

• Metadata-Driven Architecture: It is the world's first metadata-powered platform for a unified data service layer. This allows developers to focus on declarative domain modeling and business logic rather than manual API coding and tuning.

• Broad Database Connectivity: The platform is compatible with a wide variety of popular databases, including PostgreSQL, MySQL, MongoDB, SQL Server, Clickhouse, and Snowflake.

• Unified Data Aggregation: With a federated query engine and a unified semantic layer, developers can compose and fetch data from any source through a single API, eliminating the need for complex data centralization or custom experience layers.

• Automated Governance and Security: Metadata dictates the behavior of the data access layer, allowing for the easy enforcement of data governance policies. The engine automatically enforces these rules, preventing API drift and coding errors while simplifying audits.

• High Performance and Reliability: APIs are automatically deployed on a globally distributed infrastructure. It includes built-in optimizations like dataloader abstractions for N+1 batching and cache priming to ensure high-speed data fetching.

• Dramatic Time-to-Market Reduction: Users report taking clinical platforms from concept to production in just 100 days or launching from a first code commit in only 30 days. It typically offers a 3x increase in speed-to-market and a 40% reduction in API development effort.

• Advanced Developer Tools: The platform supports Hasura Actions and remote schemas for growing beyond auto-generated CRUD APIs, as well as aggregate queries to simplify complex data edge cases.