SQL is the declarative language used to define, query, change, and control data in relational databases.
SELECT name, price\nFROM products\nWHERE price < 100;Use the smallest correct statement, test it with representative data, and verify constraints and performance before production use.
A development team applies What is SQL? to a small commerce database, verifies the result, and then decides whether the same approach is safe for production data.
BEGIN;\n-- Preview the exact target set first.\nSELECT id FROM orders WHERE status = 'pending';\n-- Apply the What is SQL? operation, verify affected rows, then commit.\nCOMMIT;The schema or operation satisfies the stated rule, rejects invalid data, and can be verified with a repeatable query.
This lesson reuses picostore. Relevant tables: customers, products, orders, order_items. Keep the starter rows from the Introduction lesson so results remain comparable.
SELECT o.order_id, c.name AS customer, o.status, o.total\nFROM orders o\nJOIN customers c ON c.customer_id = o.customer_id\nWHERE o.total >= 1000\nORDER BY o.ordered_at DESC;Run the verification query, compare the returned rows with the starter data, and explain why every included or excluded row is correct.
This catalog covers the practical public SQL surface. Check the exact server-version documentation before using a vendor-specific item.
DQL — SELECT queries dataDDL — CREATE, ALTER, DROP, TRUNCATE, RENAME define structuresDML — INSERT, UPDATE, DELETE, MERGE change rowsDCL — GRANT and REVOKE control accessTCL — BEGIN, COMMIT, ROLLBACK, SAVEPOINT control transactionsWITH — defines common table expressionsSELECT — chooses expressions and columnsFROM — chooses source tablesJOIN ... ON — combines related sourcesWHERE — filters rows before groupingGROUP BY — forms groupsHAVING — filters groupsWINDOW — names reusable window definitionsORDER BY — sorts the resultLIMIT / OFFSET or FETCH — restricts returned rowsStart with a small customer table and retrieve active customers in a predictable order.
SELECT customer_id, name, email\nFROM customers\nWHERE status = 'active'\nORDER BY name;Use a CTE and a window function to rank customer revenue while keeping the query readable and testable.
WITH customer_revenue AS (\n SELECT customer_id, SUM(total_amount) AS revenue\n FROM orders\n WHERE order_status = 'completed'\n GROUP BY customer_id\n)\nSELECT customer_id, revenue,\n DENSE_RANK() OVER (ORDER BY revenue DESC) AS revenue_rank\nFROM customer_revenue\nORDER BY revenue_rank, customer_id;Use standard SQL first, then document any MySQL or PostgreSQL-specific syntax. Verify the statement with small sample data, an edge case, and the expected result before using it in production.
SQL is the declarative language used to define, query, change, and control data in relational databases.
SELECT name, price\nFROM products\nWHERE price < 100;Use the smallest correct statement, test it with representative data, and verify constraints and performance before production use.
A development team applies What is SQL? to a small commerce database, verifies the result, and then decides whether the same approach is safe for production data.
BEGIN;\n-- Preview the exact target set first.\nSELECT id FROM orders WHERE status = 'pending';\n-- Apply the What is SQL? operation, verify affected rows, then commit.\nCOMMIT;The schema or operation satisfies the stated rule, rejects invalid data, and can be verified with a repeatable query.
This lesson reuses picostore. Relevant tables: customers, products, orders, order_items. Keep the starter rows from the Introduction lesson so results remain comparable.
SELECT o.order_id, c.name AS customer, o.status, o.total\nFROM orders o\nJOIN customers c ON c.customer_id = o.customer_id\nWHERE o.total >= 1000\nORDER BY o.ordered_at DESC;Run the verification query, compare the returned rows with the starter data, and explain why every included or excluded row is correct.
This catalog covers the practical public SQL surface. Check the exact server-version documentation before using a vendor-specific item.
DQL — SELECT queries dataDDL — CREATE, ALTER, DROP, TRUNCATE, RENAME define structuresDML — INSERT, UPDATE, DELETE, MERGE change rowsDCL — GRANT and REVOKE control accessTCL — BEGIN, COMMIT, ROLLBACK, SAVEPOINT control transactionsWITH — defines common table expressionsSELECT — chooses expressions and columnsFROM — chooses source tablesJOIN ... ON — combines related sourcesWHERE — filters rows before groupingGROUP BY — forms groupsHAVING — filters groupsWINDOW — names reusable window definitionsORDER BY — sorts the resultLIMIT / OFFSET or FETCH — restricts returned rowsStart with a small customer table and retrieve active customers in a predictable order.
SELECT customer_id, name, email\nFROM customers\nWHERE status = 'active'\nORDER BY name;Use a CTE and a window function to rank customer revenue while keeping the query readable and testable.
WITH customer_revenue AS (\n SELECT customer_id, SUM(total_amount) AS revenue\n FROM orders\n WHERE order_status = 'completed'\n GROUP BY customer_id\n)\nSELECT customer_id, revenue,\n DENSE_RANK() OVER (ORDER BY revenue DESC) AS revenue_rank\nFROM customer_revenue\nORDER BY revenue_rank, customer_id;Use standard SQL first, then document any MySQL or PostgreSQL-specific syntax. Verify the statement with small sample data, an edge case, and the expected result before using it in production.