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From tsql-master
Provides complete T-SQL function reference for SQL Server and Azure SQL Database, covering string, date/time, window/ranking, aggregate, JSON/XML, and system/metadata functions with version info.
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Complete reference for all T-SQL function categories with version-specific availability.
Provides advanced T-SQL patterns for SQL Server: recursive CTEs, APPLY operator, MERGE with OUTPUT clause, temporal tables, In-Memory OLTP, and ROLLUP/CUBE/GROUPING SETS.
Writes correct, performant SQL for data warehouses like Snowflake, BigQuery, Databricks, PostgreSQL. Optimizes queries, translates dialects, uses CTEs, window functions, aggregations.
Crafts and optimizes SQL across Snowflake, BigQuery, Databricks, Redshift, and PostgreSQL. Covers window functions, CTEs, aggregations, joins, funnel queries, cohort retention, deduplication, dialect translation, and slow query tuning.
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Complete reference for all T-SQL function categories with version-specific availability.
| Function | Description | Version |
|---|---|---|
CONCAT(str1, str2, ...) | NULL-safe concatenation | 2012+ |
CONCAT_WS(sep, str1, ...) | Concatenate with separator | 2017+ |
STRING_AGG(expr, sep) | Aggregate strings | 2017+ |
STRING_SPLIT(str, sep) | Split to rows | 2016+ |
STRING_SPLIT(str, sep, 1) | With ordinal column | 2022+ |
TRIM([chars FROM] str) | Remove leading/trailing | 2017+ |
TRANSLATE(str, from, to) | Character replacement | 2017+ |
FORMAT(value, format) | .NET format strings | 2012+ |
| Function | Description | Version |
|---|---|---|
DATEADD(part, n, date) | Add interval | All |
DATEDIFF(part, start, end) | Difference (int) | All |
DATEDIFF_BIG(part, s, e) | Difference (bigint) | 2016+ |
EOMONTH(date, [offset]) | Last day of month | 2012+ |
DATETRUNC(part, date) | Truncate to precision | 2022+ |
DATE_BUCKET(part, n, date) | Group into buckets | 2022+ |
AT TIME ZONE 'tz' | Timezone conversion | 2016+ |
| Function | Description | Version |
|---|---|---|
ROW_NUMBER() | Sequential unique numbers | 2005+ |
RANK() | Rank with gaps for ties | 2005+ |
DENSE_RANK() | Rank without gaps | 2005+ |
NTILE(n) | Distribute into n groups | 2005+ |
LAG(col, n, default) | Previous row value | 2012+ |
LEAD(col, n, default) | Next row value | 2012+ |
FIRST_VALUE(col) | First in window | 2012+ |
LAST_VALUE(col) | Last in window | 2012+ |
IGNORE NULLS | Skip NULLs in offset funcs | 2022+ |
| Function | Description |
|---|---|
GREATEST(v1, v2, ...) | Maximum of values |
LEAST(v1, v2, ...) | Minimum of values |
DATETRUNC(part, date) | Truncate date |
GENERATE_SERIES(start, stop, [step]) | Number sequence |
JSON_OBJECT('key': val) | Create JSON object |
JSON_ARRAY(v1, v2, ...) | Create JSON array |
JSON_PATH_EXISTS(json, path) | Check path exists |
IS [NOT] DISTINCT FROM | NULL-safe comparison |
-- Concatenate with separator (NULL-safe)
SELECT CONCAT_WS(', ', FirstName, MiddleName, LastName) AS FullName
-- Split string to rows with ordinal
SELECT value, ordinal
FROM STRING_SPLIT('apple,banana,cherry', ',', 1)
-- Aggregate strings with ordering
SELECT DeptID,
STRING_AGG(EmployeeName, ', ') WITHIN GROUP (ORDER BY HireDate)
FROM Employees
GROUP BY DeptID
-- Truncate to first of month
SELECT DATETRUNC(month, OrderDate) AS MonthStart
-- Group by week buckets
SELECT DATE_BUCKET(week, 1, OrderDate) AS WeekBucket,
COUNT(*) AS OrderCount
FROM Orders
GROUP BY DATE_BUCKET(week, 1, OrderDate)
-- Generate date series
SELECT CAST(value AS date) AS Date
FROM GENERATE_SERIES(
CAST('2024-01-01' AS date),
CAST('2024-12-31' AS date),
1
)
-- Running total with partitioning
SELECT OrderID, CustomerID, Amount,
SUM(Amount) OVER (
PARTITION BY CustomerID
ORDER BY OrderDate
ROWS UNBOUNDED PRECEDING
) AS RunningTotal
FROM Orders
-- Get previous non-NULL value (SQL 2022+)
SELECT Date, Value,
LAST_VALUE(Value) IGNORE NULLS OVER (
ORDER BY Date
ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
) AS PreviousNonNull
FROM Measurements
-- Extract scalar value
SELECT JSON_VALUE(JsonColumn, '$.customer.name') AS CustomerName
-- Parse JSON array to rows
SELECT j.ProductID, j.Quantity
FROM Orders
CROSS APPLY OPENJSON(OrderDetails)
WITH (
ProductID INT '$.productId',
Quantity INT '$.qty'
) AS j
-- Build JSON object (SQL 2022+)
SELECT JSON_OBJECT('id': CustomerID, 'name': CustomerName) AS CustomerJson
FROM Customers
For deeper coverage of specific function categories, see:
references/string-functions.md - Complete string function reference with examplesreferences/window-functions.md - Window and ranking functions with frame specifications