SQL INSERT INTO adds new rows to a table. Provide the table name, an optional column list, then VALUES or a SELECT statement. Use multiple VALUES lists for bulk inserts or INSERT … SELECT to copy data. Always match column order and data types.
SQL INSERT INTO creates a new row in a table. You supply a table name, optional column list, and either literal values or the result of a SELECT query. The database engine validates data types, applies constraints, and writes the row to disk.
Use INSERT INTO table (column1, column2) VALUES (value1, value2);. Omitting the column list requires passing a value for every column in the table in defined order. Explicit lists avoid surprises when schemas change.
Attach additional comma-separated value lists to add several rows in one statement. This reduces round-trips and logs fewer transactions than repeating single-row inserts.
Replace the VALUES clause with a SELECT query that returns matching columns. INSERT INTO target (col1, col2) SELECT col1, col2 FROM source; copies data efficiently and respects constraints unless explicitly disabled.
Skip optional columns to let DEFAULT fire or pass NULL explicitly. Databases apply default expressions, sequences, or timestamps automatically. Inserting NULL violates NOT NULL constraints, so define defaults for required columns.
List the desired columns after the table name. Unlisted columns receive DEFAULT or NULL. Always align the number and order of VALUES with the listed columns to prevent “column count doesn’t match” errors.
Always name columns, validate data types, wrap large inserts in transactions, and batch thousands of rows to balance speed with transaction log growth. Use prepared statements or parameterized queries to prevent SQL injection.
Use database-specific features like RETURNING in PostgreSQL, OUTPUT in SQL Server, or LAST_INSERT_ID() in MySQL. These clauses return generated primary keys or computed columns immediately, eliminating race conditions.
Use RETURNING when you need the inserted row’s auto-generated values in the same round-trip. It’s ideal for web APIs that must return new resource IDs without an extra SELECT query.
Batch inserts, disable non-essential indexes, and commit in intervals. Use COPY or BULK INSERT commands for very large datasets. Ensure the transaction log has room, and consider partitioning heavily written tables.
Create a practice table, then write single-row, multi-row, and INSERT…SELECT statements. Vary column order and test error messages to cement understanding.
INSERT INTO adds rows, supports VALUES and SELECT sources, and scales via batching. Name columns, match data types, and leverage RETURNING for generated keys. Tools like Galaxy’s galaxy.io/features/ai" target="_blank" id="">AI copilot accelerate writing and sharing inserts.
No, but specifying it is safer. Omitting it requires values for every column in table order, which breaks when schemas change.
Standard SQL does not allow multi-table inserts in one command, but some databases (like Oracle’s INSERT ALL) provide extensions.
Most engines allow thousands of rows per INSERT, but practical limits depend on packet size, memory, and transaction log capacity.
It acquires row-level or page-level locks. High-volume inserts can escalate locks, so batch work and monitor contention.