GraphQL has transformed how modern applications access data by enabling flexible, efficient, and precise queries. As systems evolve toward microservices, multi-database architectures, and AI-driven workloads, the need for a more native and simplified data access layer has become critical.

With Oracle AI Database 26ai (23.26), Oracle introduces native GraphQL support directly inside the database. With the new GraphQL() table function, developers can use GraphQL syntax to query relational data without the need of any external middleware. The database automatically translates GraphQL queries into optimized SQL and returns JSON-formatted responses.

Oracle has also enhanced GraphQL directives for JSON Duality Views and enabled GraphQL exposure through ORDS RESTful endpoints, making GraphQL a first-class, database-native option for modern API development.

What’s New: Key Enhancements in GraphQL 26ai

Native GraphQL Execution Inside the Oracle AI Database

GraphQL queries are now executed natively within the database , eliminating the need for external GraphQL servers or middleware. Refer link for more information

Direct GraphQL queries on relational tables

Database objects such as tables and views can be queried using GraphQL syntax, with results automatically returned as JSON-formatted responses.

Enhanced directives and JSON Duality View integration

New and improved GraphQL directives provide seamless access to both relational and JSON data through JSON Duality Views.

Support for WHERE clauses and SQL predicates

Where clause and SQL-style filtering is now supported within GraphQL Query-by-Example, enabling expressive and precise data filtering at the GraphQL layer.

Improved query readability and schema awareness

GraphQL queries support inline comments and fully recognize table and column names, making queries easier to read, maintain, and align with database schemas.

Key Benefits

With these enhancements in GraphQL 26ai, Oracle delivers a developer-friendly data access model that significantly lowers complexity while preserving enterprise-grade capabilities

  • One of the major benefits is,  it’s especially useful for developers who are less familiar with SQL. Instead of writing complex joins and nested queries, developers can express data requirements using intuitive GraphQL syntax.
  • GraphQL follows a “what-you-see-is-what-you-get” query model — meaning the structure of your query directly matches the structure of the data returned. With GraphQL, users don’t need to understand complex SQL joins or query syntax — developers can simply describe the data they need, and Oracle takes care of the rest.
  • No middleware or custom API layer required. Oracle’s supports open-standard GraphQL syntax, fully compatible with popular GraphQL ecosystems. The feature allows developers to connect directly to Oracle AI Database and start querying data immediately—without building or maintaining additional REST APIs, resolvers, or data adapters
  • Enterprise Standard and future -proof. Oracle’s GraphQL support is fully aligned with the open GraphQL specification, combining the flexibility of a modern API standard with the reliability, security, and performance of Oracle AI Database. Developers get the best of both worlds—enterprise data management with modern API simplicity.

Why it matters:

  • This brings a major simplification in application development.
  • Instead of creating and maintaining separate REST APIs or ORMs, front-end teams can now directly
    query the database using GraphQL queries and mutations.
  • It’s secure, schema-aware, and performance-tuned — offering a unified data access layer that leverages Oracle’s strengths in both JSON and relational worlds.

What’s Next?

In the next article, I’ll walk through practical GraphQL examples that demonstrate how native GraphQL queries in Oracle AI Database can be used as direct equivalents to traditional SQL like subqueries and joins using real-world table relationships—showing how complex relational logic can now be expressed cleanly and intuitively through GraphQL.