JSON Literals

Express shapes like you're writing JSON.

SELECT { email, mobile: phone } AS contact FROM users;

LinkedQL translates that to the dialect-native JSON function.

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Overview

SQL expresses shapes via JSON functions. Their imperative nature often complicates that very use case: expressing shapes.

LinkedQL restores the conventional object thinking with first-class support for JSON literals. These let you express structure the way you’d write JSON itself — each being the structure itself rather than an instruction for how to construct it.

JSON literals are purely syntactic convenience over the function paradigm:

Literal	PostgreSQL Function	MySQL Function
{ ... }	JSON_BUILD_OBJECT()	JSON_OBJECT()
[ ... ]	JSON_BUILD_ARRAY()	JSON_ARRAY()
AS alias[]	JSON_AGG()	JSON_ARRAYAGG()

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Modeling Objects and Arrays

In place of long function calls, object and array literals make modeling structure in SQL concise and expressive.

Object Literals ({ ... })

The object notation { ... } is an expression that resolves to JSON_BUILD_OBJECT() in PostgreSQL, and JSON_OBJECT() in MySQL.

SELECT { name: full_name, email: email } AS user
FROM users;

SELECT JSON_BUILD_OBJECT('name', full_name, 'email', email)
FROM users;

If you omit the key, the column name becomes the key automatically.

SELECT { full_name, email } AS user
FROM users;

Object literals can appear in projections, expressions, or subqueries — anywhere their function counterparts can.

Array Literals ([ ... ])

The array notation [ ... ] is an expression that resolves to JSON_BUILD_ARRAY() in PostgreSQL, and JSON_ARRAY() in MySQL.

SELECT [ full_name, email ] AS contact_list
FROM users;

SELECT JSON_BUILD_ARRAY(full_name, email)
FROM users;

Arrays, like objects, can appear wherever their function counterparts can.

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Aggregation Syntax

In place of explicit aggregation functions, LinkedQL lets you declare an aggregated result using the postfix collection notation.

Postfixed Aliases

Annotate output aliases with the postfix collection notation — alias[] — to aggregate expressions into collections.

This is a shorthand for JSON_AGG(), or JSON_ARRAYAGG() in MySQL.

SELECT
  u.id,
  u.title AS titles[]
FROM users AS u
LEFT JOIN posts AS p ON p.author = u.id
GROUP BY u.id;

SELECT
  u.id,
  JSON_AGG(u.title) AS titles
FROM users AS u
LEFT JOIN posts AS p ON p.author = u.id
GROUP BY u.id;

titles becomes an array containing all title values for that group.

Collection Fields

Like the previous, annotate object fields with the postfix collection notation — key[] — to aggregate expressions into collections.

SELECT
  u.id,
  { name, posts[]: { id: p.id, title: p.title } } AS profile
FROM users AS u
LEFT JOIN posts AS p ON p.author = u.id
GROUP BY u.id, u.name;

This form aggregates each user’s posts into a single object literal, producing nested, relational JSON structures inline.

Grouping Rules (PostgreSQL & MySQL)

LinkedQL’s aggregation syntax doesn’t alter SQL’s grouping rules.

• In PostgreSQL, all non-aggregated columns must appear in GROUP BY.
• In MySQL, when ONLY_FULL_GROUP_BY is enabled (recommended), the same rule applies.

It simplifies expression, not semantics.

An exception to this rule appears in DeepRefs — where the aggregation syntax isolates its own grouping semantics from the main query.

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Composition & Integration

JSON literals are first-class expressions in LinkedQL’s language surface; they nest within each other and integrate seamlessly with relational constructs like DeepRefs.

Nesting

Objects and arrays can nest freely, allowing structured projections of any shape.

SELECT
  id,
  {
    name,
    contact: { email, phone },
    tags: [ tag1, tag2 ]
  } AS profile
FROM users;

DeepRefs

JSON literals compose with DeepRefs to model relationships structurally.

SELECT
  p.id,
  p.title,
  p.author ~> { id, name, email } AS author,
  { comments[]: (post <~ comments) ~> { id, text } } AS related
FROM posts AS p;

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Additional Reading

If you want to learn about...	Go to...
the related relationship traversal syntax	DeepRefs
the broader LinkedQL language surface	Language Surface