Fauna Schema Languange brings data consistency to document databases

Fauna Schema Languange brings data consistency to document databases

Fauna addresses a fundamental problem that developers face when building GenAI, edge and IoT applications; ensuring data consistency and security at scale in document databases.

Fauna provides a document relational database, which users can access via an API. The database combines two database architectures: relational and document model. Data is stored in JSON documents.

Today, Fauna announces a proprietary schema language. This adds a property of the relational model. Many useful features of that model still appear to be missing from Fauna’s document relational database. “Document databases proved the many benefits of being developer-friendly and flexible, but lack many of the key features inherent in relational databases, including powerful relational query capabilities, ACID compliance and schema enforcement,” states Hassen Karaa, VP of Product at Fauna.

Fauna Schema Language

The Fauna Schema Language (FSL) allows developers to define several things in plain language. These include domain models, access control and business logic. Developers should get a familiar feel by using their database schema just like application code.

Document Types also allow for the definition of schema structures and the automation of testing. On GitHub, for example, testing can be triggered from the moment a new schema version is implemented. Usually, this implementation is characterized by app downtime, but this is prevented by the introduction of Zero-Downtime Migrations. The feature allows migrations to be run as code with FSL and streamlined with the CI/CD pipelines involved.

Also read: Oracle Database 23ai brings data and AI together