Summary: JSON_VALUE(), introduced in PostgreSQL 17, extracts a single scalar value from a JSON or JSONB input using a SQL/JSON path expression, with optional type conversion via RETURNING and configurable ON EMPTY and ON ERROR clauses. Use it instead of JSON_QUERY() when you need a plain text or typed scalar result (number, date, boolean) rather than a JSON object or array, and when missing or invalid values must return a default instead of raising an error.

Extract and Convert JSON Scalar Values

The JSON_VALUE() function introduced in PostgreSQL 17 provides a specialized way to extract single scalar values from JSON data with type conversion capabilities. Use it when you need to extract and potentially convert individual values from JSON structures while ensuring type safety and proper error handling.

Use JSON_VALUE() when you need to:

• Extract single scalar values from JSON
• Convert JSON values to specific PostgreSQL data types
• Ensure strict type safety when working with JSON data
• Handle missing or invalid JSON values gracefully

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The JSON_VALUE() function uses the following syntax:

JSON_VALUE(
    context_item,                    -- JSON input
    path_expression                  -- SQL/JSON path expression
    [ PASSING { value AS varname } [, ...] ]
    [ RETURNING data_type ]         -- Optional type conversion
    [ { ERROR | NULL | DEFAULT expression } ON EMPTY ]
    [ { ERROR | NULL | DEFAULT expression } ON ERROR ]
) → text

Parameters:

• context_item: JSON/JSONB input to process
• path_expression: SQL/JSON path expression that identifies the value to extract
• PASSING: Optional clause to pass variables into the path expression
• RETURNING: Specifies the desired output data type (defaults to text)
• ON EMPTY: Handles cases where no value is found
• ON ERROR: Handles extraction or conversion errors

Let's explore various ways to use the JSON_VALUE() function with different scenarios and options.

-- Extract a simple string value
SELECT JSON_VALUE('{"name": "Alice"}', '$.name');

# |  json_value
--------------
1 | Alice

-- Extract a numeric value
SELECT JSON_VALUE('{"age": 30}', '$.age');

# | json_value
-------------
1 | 30

-- Convert string to float
SELECT JSON_VALUE(
    '"123.45"',
    '$'
    RETURNING float
);

# | json_value
-------------
1 | 123.45

-- Convert string to date
SELECT JSON_VALUE(
    '"2024-12-04"',
    '$'
    RETURNING date
);

# | json_value
-------------
1 | 2024-12-04

-- Extract array element using variable
SELECT JSON_VALUE(
    '[1, 2, 3, 4, 5]',
    'strict $[$index]'
    PASSING 2 AS index
);

# | json_value
-------------
1 | 3

-- Handle missing values with DEFAULT
SELECT JSON_VALUE(
    '{"data": null}',
    '$.missing_field'
    DEFAULT 'Not Found' ON EMPTY
);

# |  json_value
---------------
1 | Not Found

-- Handle conversion errors
SELECT JSON_VALUE(
    '{"value": "not a number"}',
    '$.value'
    RETURNING numeric
    DEFAULT 0 ON ERROR
);

# | json_value
-------------
1 | 0

-- Extract from nested object
SELECT JSON_VALUE(
    '{
        "user": {
            "contact": {
                "email": "alice@example.com"
            }
        }
    }',
    '$.user.contact.email'
);

# |      json_value
----------------------
1 | alice@example.com

-- Validate email format
CREATE TABLE user_emails (
    id SERIAL PRIMARY KEY,
    user_data jsonb,
    CONSTRAINT valid_email CHECK (
        JSON_VALUE(user_data, '$.email' RETURNING text)
        ~ '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$'
    )
);

-- This insert will succeed
INSERT INTO user_emails (user_data)
VALUES (
    '{"name": "John Doe", "email": "john.doe@example.com"}'
);

-- This insert will fail
INSERT INTO user_emails (user_data)
VALUES (
    '{"name": "Alice", "email": "invalid-email"}'
);

The function provides several ways to handle errors:

1. Using ON EMPTY:

   • ERROR: Raises an error (default)
   • NULL: Returns NULL
   • DEFAULT expression: Returns specified value

2. Using ON ERROR:

   • ERROR: Raises an error (default)
   • NULL: Returns NULL
   • DEFAULT expression: Returns specified value

The JSON_VALUE() function is designed for extracting scalar values from JSON data, while JSON_QUERY() is used for extracting JSON structures (objects, arrays, or scalar values). Here's a comparison of the two functions:

JSON_VALUE():

• Designed specifically for extracting scalar values (numbers, strings, booleans)
• Always returns a single scalar value as text (or specified type via RETURNING)
• Removes quotes from string values by default
• Throws an error if the result is an object or array

JSON_QUERY():

• Designed for extracting JSON structures (objects, arrays, or scalar values)
• Returns valid JSON/JSONB output
• Preserves quotes on string values by default
• Can handle multiple values using wrapper options

-- Working with scalar string values
SELECT
    JSON_VALUE('{"name": "Alice"}', '$.name') as value_result,
    JSON_QUERY('{"name": "Alice"}', '$.name') as query_result;

# | value_result | query_result
--------------------------------
1 | Alice        | "Alice"

-- Working with arrays (JSON_VALUE will error and give null by default)
SELECT
    JSON_VALUE('{"tags": ["sql", "json"]}', '$.tags' NULL ON ERROR) as value_result,
    JSON_QUERY('{"tags": ["sql", "json"]}', '$.tags') as query_result;

# |  value_result |       query_result
---------------------------------------
1 |               | ["sql", "json"]

1. Type safety:

   • Always use RETURNING when specific data types are expected
   • Implement appropriate error handling for type conversions

2. Performance considerations:

   • Use indexes on frequently queried JSON paths

• PostgreSQL JSON functions documentation
• SQL/JSON path language

• array_to_json
• json
• json_agg
• json_array_elements
• json_build_object
• json_each
• json_exists
• json_extract_path
• json_extract_path_text
• json_object
• json_populate_record
• json_query
• json_scalar
• json_serialize
• json_table
• json_to_record
• jsonb_array_elements
• jsonb_each
• jsonb_extract_path
• jsonb_extract_path_text
• jsonb_object
• jsonb_populate_record
• jsonb_to_record

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