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JSON-Relational Duality Views let you expose your relational tables as flexible JSON documents — and update them both ways — without any data duplication. Here’s a practical, step-by-step guide to creating them.

Why Create Duality Views?

• Developers get simple JSON documents for modern apps
• DBAs keep normalized, relational tables for consistency and analytics
• Both views work on the exact same underlying data

Simple Duality View Example (Department)

-- 1. Create the underlying relational table
CREATE TABLE dept_tab (
    deptno    NUMBER(2,0) PRIMARY KEY,
    dname     VARCHAR2(14),
    code      NUMBER(13,0),
    state     VARCHAR2(15),
    country   VARCHAR2(15)
);

-- 2. Create the Duality View
CREATE JSON RELATIONAL DUALITY VIEW dept_dv AS
  SELECT JSON { '_id'      : d.deptno,
                'deptName' : d.dname,
                'location' : { 'zipcode' : d.code,
                               'country' : d.country }
    FROM dept_tab d
    WITH UPDATE INSERT DELETE;

This view now supports clean JSON documents while the data stays normalized in the table.

More Complex Example: Orders with Nested Data

CREATE OR REPLACE JSON RELATIONAL DUALITY VIEW orders_ov AS
SELECT JSON { '_id'          : ord.order_id,
              'orderTime'    : ord.order_datetime,
              'orderStatus'  : ord.order_status,
              'customerInfo' : (SELECT JSON { 'customerId'   : cust.customer_id,
                                             'customerName' : cust.full_name,
                                             'customerEmail': cust.email_address }
                                FROM customers cust 
                                WHERE cust.customer_id = ord.customer_id),
              'orderItems'   : (SELECT JSON_ARRAYAGG(
                                   JSON { 'orderItemId' : oi.line_item_id,
                                          'quantity'    : oi.quantity,
                                          'productInfo' : ...,
                                          'shipmentInfo': ... }
                                 ) 
                                 FROM order_items oi 
                                 WHERE ord.order_id = oi.order_id)
    }
FROM orders ord
WITH INSERT UPDATE DELETE;

Controlling Updatability

Use the WITH clause to control what operations are allowed:

• WITH INSERT UPDATE DELETE — Fully updatable (default for root table)
• WITH NOINSERT NODELETE NOUPDATE — Read-only
• You can override at column level: WITH NOUPDATE or WITH UPDATE

Key Rules for Duality Views

• Every underlying table needs at least one identifying column (primary key, unique key, or identity column)
• Use nested subqueries for 1-to-N relationships → becomes a JSON array
• Use UNNEST for 1-to-1 relationships to merge into the same object
• Supported column types include VARCHAR2, NUMBER, DATE, JSON, VECTOR, etc.
• Each duality view has a single DATA column of type JSON

Automatic Metadata Fields

Every document automatically includes:

{
  "_metadata": {
    "etag": "abc123...",     -- for optimistic concurrency
    "asof": 1234567890       -- system change number (SCN)
  }
}

Best Practices

• Start with simple single-table views to learn the pattern
• Use meaningful field names in JSON (not just column names)
• Combine with AI Vector Search or Private Agent Factory for powerful AI apps
• Always test updates through both the document view and relational tables

Conclusion

Creating JSON-Relational Duality Views is straightforward with a simple SQL statement. You get the best of both worlds: document flexibility for modern apps and relational power for analytics and integrity — all on the same data.