600+ SQL Interview Questions for 2025

Learn how to use the cast function to convert salary data stored as strings into numeric types by casting to float and then to integer, including handling decimals.

Explore SQL aliases with the as keyword to rename columns and tables, apply aliases across single or multiple columns, and troubleshoot alias usage in queries.

Master limit and offset to control query results. Use limit to fetch the first five rows and offset to skip rows and retrieve subsequent ranges from the product table.

Explore filtering string columns with the like keyword, using % and _ wildcards to match starts with, ends with, or contains patterns in product names.

Filter boolean columns with the where clause to retrieve active products, using true or 1 for true and false or 0 for false, and combine conditions with and and or.

Explore the between clause to filter numeric and date columns, including endpoints. See price between 49.99 and 200.99 and order date between 1st January 2024 and 5th January 2024.

Learn to use group by with having to filter aggregated category totals, summing prices and stock, and apply multiple conditions beyond where.

Learn to use the where clause with group by to filter groups before aggregation, using price > 200 and active = true on product name, price, and is active.

Explore how the union operator in SQL combines results from two tables, removes duplicate values, and consolidates employee data from multiple sources.

Explore the intersect operator in SQL by comparing two tables to return only common rows and matching columns, while contrasting with union and removing duplicates.

Learn how to use subqueries to filter data dynamically with inner queries, the in clause, and distinct product IDs from orders to retrieve sold products.

Sort data with the order by clause in SQL, mastering ascending and descending order on product name and price, and multi-column sorting like product name with stock.

Explore window aggregate functions to compute running totals, moving averages, and percentages of total across rows, using over with partition by and order by for department and overall insights.

Explore common table expressions (ctes) in sql, using the with keyword to create a temporary result set that improves readability and enables reuse and recursive operations.

Learn to write recursive cte queries that generate numbers from 1 to 10 using a base case, union all, and a stop condition to prevent infinite loops and retrieve results.

Explore recursive ctes to build an employee hierarchy and retrieve direct and indirect reports. Learn how to use union all and level tracking to traverse managers up to the top.

Learn how to implement range partitioning by date to create partitioned tables, automatically route data, and query specific partitions for faster time-based analytics.

Explore range partitioning and partition pruning to accelerate queries by scanning only relevant partitions, using the sale date as the partition key.

Explore list partitioning to divide data by discrete region values, and learn to create a main partitioned table with North and South region partitions and automatic data routing.

Harness list partitioning by region to enable partition pruning, so the optimizer scans only the north or south partition when filtering on region.

Explore arrays in PostgreSQL, learning how to store multiple values in a single column and create array columns. Learn to insert, query, and retrieve specific indices for marks and subjects.

Explore arrays with aggregate functions in SQL; compute array lengths with array_length, and sum scores by unnesting the marks array via a subquery to get total marks per student.

Explore arrays in SQL with the all and any operators in the where clause to filter data by every or at least one element in a multi-value column.

Learn how to create and use SQL views, a virtual table that forwards queries to the underlying table, enabling column and row filtering for security and data subset.

Explore case statements in SQL to implement conditional logic and categorize products by price and active status, using basic and advanced case statements, including or conditions for dynamic results.

Explore the coalesce function to gracefully handle null values in SQL, replacing null emails with no email and salaries with zero in an employee table.

Learn how the null if function handles conditional nulls in SQL by replacing specific salaries with null. See practical employee table examples with 75,000, 70,000, and 55,000.