SQL Server 2025 NEWS: Enhanced T-SQL Syntax for Query Modularity

Enhanced T-SQL Syntax for Query Modularity

One of the most interesting directions for SQL Server 2025 is the evolution of T-SQL towards more modular, readable, and composable queries.

The goal is not to replace stored procedures or functions, but to allow developers to structure complex queries into logical blocks, very much like local functions or expressions, while keeping everything inside a single SQL statement.

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The Problem: Complex Queries Become Hard to Read

Consider a simple table:

ARTICO (
    CODICE INT,
    DESCR  VARCHAR(100)
)

Even with a small table like ARTICO, real-world queries often grow in complexity: filters, derived columns, joins, business rules, and conditional logic all accumulate.

Traditionally, we rely on deeply nested subqueries or long WITH chains, which quickly become hard to read and maintain.

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Traditional Approach (Classic CTE)

Using today’s T-SQL, we might write:

WITH ArticoliFiltrati AS (
    SELECT CODICE, DESCR
    FROM ARTICO
    WHERE CODICE > 100
),
ArticoliNormalizzati AS (
    SELECT
        CODICE,
        UPPER(DESCR) AS DESCR
    FROM ArticoliFiltrati
)
SELECT *
FROM ArticoliNormalizzati;

This works, but as logic grows, the intent of each step can become blurred.

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Enhanced Modular Syntax (SQL Server 2025 Direction)

SQL Server 2025 introduces the concept of named query blocks, allowing us to explicitly define logical units of work inside a query.

Conceptually, the same query could be expressed as:

WITH
  DEFINE FilteredArticoli = (
      SELECT CODICE, DESCR
      FROM ARTICO
      WHERE CODICE > 100
  ),
  DEFINE NormalizedArticoli = (
      SELECT
          CODICE,
          UPPER(DESCR) AS DESCR
      FROM FilteredArticoli
  )
SELECT *
FROM NormalizedArticoli;

Each block has a clear name and a clear responsibility, very similar to local functions in a programming language.

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Why This Matters

• Improved readability: each block expresses intent, not just mechanics
• Better maintainability: logic can be modified in isolation
• Fewer nested subqueries: flatter, more understandable SQL
• Closer to declarative programming: describe what, not how

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More Advanced Example: Business Logic on ARTICO

Let’s introduce a slightly more realistic scenario:

• Filter valid articles
• Classify them based on the code
• Prepare a final projection for reporting

WITH
  DEFINE ValidArticoli = (
      SELECT CODICE, DESCR
      FROM ARTICO
      WHERE DESCR IS NOT NULL
  ),
  DEFINE ClassifiedArticoli = (
      SELECT
          CODICE,
          DESCR,
          CASE
              WHEN CODICE < 1000 THEN 'STANDARD'
              ELSE 'SPECIAL'
          END AS CATEGORY
      FROM ValidArticoli
  )
SELECT CODICE, DESCR, CATEGORY
FROM ClassifiedArticoli;

This query reads almost like a specification: each step refines the data without hiding logic in deeply nested expressions.

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Not a New Language – An Evolution of T-SQL

It’s important to stress that this approach does not turn T-SQL into a procedural language.

Instead, it strengthens its declarative nature, making complex data transformations easier to express, review, and reason about.

For developers working on large SQL codebases, this is a major step forward.

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Why This Fits Modern SQL Workloads

As SQL Server increasingly intersects with:

• Analytics
• Data science
• AI-driven query optimization

the ability to express logic in a clean, modular way becomes crucial.

Enhanced query modularity is not about syntax sugar — it is about scaling human understanding of SQL.