Modern applications generate and consume massive amounts of JSON data, from web services and APIs to IoT devices and microservices. Traditionally, working with JSON in an enterprise database required complex transformations or hybrid document-relational architectures. Our team’s experience with Oracle AI Database 26ai shows how JSON can be native, performant, and enterprise-ready, while still giving engineers full control.

JSON as a First-Class Citizen

In 26ai, JSON is fully integrated into the database engine. Documents can be stored in BLOB, CLOB, or VARCHAR2 columns, validated automatically, and queried with powerful SQL and PL/SQL constructs. Newer versions even allow explicit JSON typed columns, combining the flexibility of schemaless documents with the power of Oracle’s transactional engine.

• Validation at insert/update ensures only valid JSON is stored
• Optimized storage compresses JSON automatically
• Native support allows full CRUD, indexing, and query capabilities

Dual Access with JSON-Relational Views

One of 26ai’s standout features is JSON-Relational Duality Views, which let the same underlying data appear as either JSON documents or relational rows and columns.

• Data stored relationally can be queried or updated as JSON
• Views are updatable, so JSON clients can insert or modify data without touching relational schemas
• Reduces the need for ORMs or transformation layers

This makes 26ai ideal for teams working on both document-centric applications and traditional analytics.

Advanced JSON Functions and Indexing

26ai provides a rich set of SQL/JSON functions:

• JSON_TRANSFORM supports nested paths, array manipulation, and arithmetic operations
• JSON_VALUE, JSON_QUERY, and JSON_EXISTS allow precise querying
• JSON_ID generates unique identifiers for documents
• Search indexes speed up queries by indexing JSON paths selectively

These features allow the team to explore, transform, and analyze JSON data efficiently, without compromising performance.

Hybrid Workflows with JSON Collections

The database supports JSON collection tables, where each row is a JSON document. These can be queried with SQL or accessed via SODA APIs or MongoDB-compatible drivers.

• Enables seamless integration with application code
• Works alongside relational tables for analytics and reporting
• Supports external table ingestion for newline-delimited JSON or arrays

Built-In Enterprise Features

Oracle AI Database 26ai brings JSON into the enterprise world:

• Replication and logging can track only modified regions of JSON, improving performance
• Data dictionary views give visibility into indexes and virtual columns
• Session-level parameters control SQL/JSON behavior for fine-tuned workloads
• Native GraphQL support returns JSON from relational and duality views, enabling modern API-driven applications

Looking Ahead

JSON in 26ai is not just about storage; it is about enterprise-scale, high-performance JSON workloads. By combining relational power, native JSON support, indexing, and modern API integration, teams can:

• Build document-centric applications without giving up transactions or analytics
• Integrate JSON with relational analytics and AI/ML pipelines
• Explore data with AI-assisted tools while keeping engineers in control
• Prepare for hybrid Lakehouse or multi-model architectures

Conclusion

Oracle AI Database 26ai makes JSON a first-class citizen in enterprise applications. Our team is leveraging these features to accelerate development, simplify data pipelines, and integrate AI and analytics seamlessly. JSON workloads that once required multiple systems and complex ETL processes can now live natively in a single, fully managed, highly performant database.

For modern applications, 26ai proves that flexible, document-driven data and enterprise-grade relational capabilities can coexist and deliver real business value.