INSERT syntax patterns: (1) Single: INSERT INTO table (col1, col2) VALUES (val1, val2) - adds 1 row. (2) Bulk: INSERT INTO table VALUES (row1), (row2), (row3) - adds multiple rows, 10-100x faster. (3) INSERT...SELECT: INSERT INTO table SELECT * FROM source WHERE condition - copies data from query. (4) RETURNING: INSERT...RETURNING col1, col2 (PostgreSQL) - returns inserted data. (5) OUTPUT: INSERT...OUTPUT INSERTED.col1 (SQL Server) - captures inserted rows. (6) COPY: COPY table FROM file (PostgreSQL) - fastest bulk load. (7) LOAD DATA: LOAD DATA INFILE (MySQL) - fast CSV import. (8) BULK INSERT: BULK INSERT table FROM file (SQL Server) - high-speed import.

Single INSERT: INSERT INTO table (col1, col2) VALUES (val1, val2) - adds 1 row, simple but slow for many rows

Bulk INSERT: INSERT INTO table VALUES (row1), (row2), (row3) - adds multiple rows in 1 statement, 10-100x faster

INSERT...SELECT: INSERT INTO target SELECT * FROM source WHERE condition - copies data from query, 100x faster than row-by-row

RETURNING (PostgreSQL): INSERT...RETURNING col1, col2 - returns inserted data without extra SELECT

OUTPUT (SQL Server): INSERT...OUTPUT INSERTED.col1, INSERTED.col2 - captures inserted rows

LAST_INSERT_ID (MySQL): SELECT LAST_INSERT_ID() after INSERT - gets last auto-increment ID

COPY (PostgreSQL): COPY table FROM file WITH (FORMAT csv) - fastest bulk load, 100x faster than INSERT

LOAD DATA (MySQL): LOAD DATA INFILE file INTO TABLE table - fast CSV import

BULK INSERT (SQL Server): BULK INSERT table FROM file - high-speed import

RETURNING clause returns inserted data, COPY for fastest bulk load, UNLOGGED tables for fast writes, ON CONFLICT for upsert

LAST_INSERT_ID() for auto-increment, LOAD DATA INFILE for bulk load, ON DUPLICATE KEY UPDATE for upsert, max_allowed_packet limits bulk size

OUTPUT clause captures inserted rows, BULK INSERT for fast import, MERGE for upsert, 1000 row limit per VALUES clause

RETURNING INTO for PL/SQL, SQL*Loader for bulk load, MERGE for upsert, multi-table INSERT (INSERT ALL)

Core references in this topic include WHERE, =, <, >, <=, >=. Learn what each one does, when to use it, and the execution or engine rules that matter.

WHERE

Filters rows before projection and sorting. It decides which rows continue through the query pipeline.

SELECT ... FROM table WHERE condition;

Most performance issues start with a weak WHERE clause or a missing supporting index.

=

Returns rows where the left and right values are exactly equal.

column = value

Use with exact matches. Do not use = NULL.

<, >, <=, >=

Range comparison operators for less-than, greater-than, and inclusive boundary checks.

salary >= 80000

IS NULL / IS NOT NULL

Tests whether a value is missing. SQL NULL semantics require dedicated NULL predicates.

manager_id IS NULL

Never use = NULL or != NULL.

BETWEEN

Checks whether a value falls inside an inclusive lower/upper range.

order_total BETWEEN 100 AND 500

ANY / ALL

Compares one value against every or at least one value from a subquery result.

salary > ALL (SELECT salary FROM interns)

TIME

Stores a time-of-day value without any date component.

TIME '14:30:00'

TIMESTAMP