LeetCode SQL: Complete Guide to Database Problems

SQL proficiency has become a non-negotiable skill in technical interviews, especially for data engineering, backend, and full-stack roles. Companies like Meta, Amazon, and Google now include dedicated SQL rounds that test your ability to write efficient queries under time pressure.

Unlike algorithm problems where you choose your language, SQL rounds test a specific skill set: joins, aggregations, window functions, and query optimization. Candidates who skip SQL preparation often find themselves stuck on problems that would be straightforward with practice.

LeetCode hosts over 200 SQL problems across Easy, Medium, and Hard difficulties. The platform supports MySQL, PostgreSQL, MS SQL Server, and Oracle, giving you flexibility to practice in the dialect your target company uses.

LeetCode organizes SQL problems into several core categories that map directly to interview question types. Understanding these categories helps you build a systematic practice plan rather than solving problems randomly.

SELECT basics and filtering form the foundation. These Easy-level problems test WHERE clauses, LIKE patterns, CASE expressions, and NULL handling. Start here if you are new to SQL on LeetCode.

JOIN operations are the most heavily tested category, appearing in over 40% of LeetCode SQL problems. You need to be comfortable with INNER JOIN, LEFT JOIN, self-joins, and multi-table joins that chain three or more tables together.

Subqueries and Common Table Expressions (CTEs) appear frequently in Medium and Hard problems. CTEs are especially important because they make complex queries readable and are the preferred approach at most companies.

The most effective way to progress through LeetCode SQL is to build skills layer by layer. Jumping straight to Hard problems leads to frustration and shallow understanding of the patterns you need.

Start with 15-20 Easy problems to build confidence with SELECT, WHERE, and basic JOINs. These problems rarely take more than 5 minutes once you know the syntax, but they reinforce habits you will rely on in harder problems.

Move to Medium problems once you can solve Easy problems without looking up syntax. Medium SQL problems introduce multi-step reasoning: joining three tables, using window functions for ranking, or writing CTEs that break a complex question into parts.

Hard SQL problems test advanced techniques like recursive CTEs, complex window function combinations, and performance-aware query writing. Most interviewers draw from Medium-level patterns, so mastering Medium thoroughly is more valuable than struggling through every Hard problem.

LeetCode supports multiple SQL dialects, and the one you choose affects both your syntax options and how your solutions are evaluated. The three most common choices are MySQL, PostgreSQL, and Oracle (PL/SQL).

MySQL is the default dialect on LeetCode and the most widely used by the community. It has the largest number of accepted solutions and discussion posts, making it the easiest dialect to find help with when you get stuck.

PostgreSQL offers richer functionality, including better window function support, array types, and more standard-compliant SQL. If your target company uses Postgres (common at startups and data-focused companies), practicing in PostgreSQL is the smart choice.

Oracle and MS SQL Server are less common on LeetCode but relevant for enterprise and finance roles. PL/SQL has unique syntax for hierarchical queries (CONNECT BY) that does not transfer to other dialects, so only invest time here if your target role specifically requires Oracle.

These 30 problems cover the most frequently tested SQL patterns in interviews. They are organized by category so you can work through them systematically rather than jumping between unrelated topics.

For JOIN practice, start with problems like Combine Two Tables (#175), Employees Earning More Than Their Managers (#181), and Department Highest Salary (#184). These build your muscle memory for the JOIN syntax you will use repeatedly.

Window function problems are essential for Medium and Hard interviews. Rank Scores (#178), Department Top Three Salaries (#185), and Consecutive Numbers (#180) teach you ROW_NUMBER, DENSE_RANK, and LAG/LEAD patterns that appear constantly.

Aggregation problems like Second Highest Salary (#176), Nth Highest Salary (#177), and Customers Who Never Order (#183) test your ability to combine GROUP BY with subqueries or LIMIT/OFFSET — a pattern that trips up candidates who only practice basic SELECT.

LeetCode now offers a Pandas track alongside its SQL problems, allowing you to solve database-style questions using Python. This is particularly relevant for data science and machine learning roles where Pandas is the expected tool.

The Pandas solutions use DataFrames instead of tables, with operations like merge() for JOINs, groupby() for aggregation, and apply() for row-level transformations. If you already know Python well, the Pandas syntax can feel more intuitive than SQL for certain problem types.

However, solving problems in Pandas does not replace SQL practice for backend and data engineering interviews. Most companies expect you to demonstrate SQL fluency in a SQL-specific round, and translating between Pandas and SQL is not always straightforward.

The most strategic approach is to solve each problem in SQL first, then attempt it in Pandas if your target role involves data analysis. This dual practice builds flexibility and helps you recognize when one tool is more natural than the other.

A structured schedule prevents the common trap of solving random problems without building real skill. This 4-week plan assumes 30-45 minutes of practice per day, five days per week.

The key to retention is spaced repetition. After solving a problem, mark it and revisit it 3 days later, then 7 days later. Problems you can solve quickly on review get longer intervals. Problems that trip you up again get shorter intervals.

Track your progress using a spreadsheet or tool like YeetCode that supports flashcard-based review. Knowing which patterns you have mastered versus which still need work lets you allocate your remaining study time efficiently.