Solve a new SQL challenge every day and practice joins, aggregations, filters, window functions, and interview-style query logic in your browser.
This page works best when you want steady SQL reps. It is not the same job as a lesson page and not exactly the same job as an interview problem bank either.
Daily problems are best when the goal is consistent practice and pattern recognition instead of a guided explanation from first principles.
If a challenge exposes a weak concept, the lesson path is usually the better place to rebuild understanding from the ground up.
Interview pages are a better fit when you specifically want company-style SQL questions and longer-form problem framing.
A strong daily problem is not random busywork. It usually trains one or two specific patterns: filtering correctly, grouping correctly, joining tables without duplication, or using window functions when ranking and comparisons matter.
Example Prompt
Find the total revenue per customer for completed orders only, then rank customers from highest to lowest revenue.
Example Solution Shape
SELECT
customer_id,
SUM(amount) AS total_revenue,
RANK() OVER (ORDER BY SUM(amount) DESC) AS revenue_rank
FROM orders
WHERE status = 'completed'
GROUP BY customer_id;A daily challenge is one rep, not the whole training plan. Use these paths to go deeper when a problem exposes a real weakness in your SQL reasoning.
Performance
Best when the query already exists and you need to understand why it is slow, what the planner is doing, and which anti-patterns to remove first.
Data Conversion
Use this path when payloads, spreadsheets, or seed files need to become relational inserts quickly without writing one-off scripts.
Schema Design
Useful when the hard part is table structure, relationships, migration impact, or how to explain a schema clearly before implementation.
Advanced SQL
A good path when the challenge is less about syntax and more about understanding multi-step logic, CTEs, window functions, and interview-style problem solving.
Learning SQL (Structured Query Language) is similar to learning a spoken language or playing an instrument. While you can understand the theory by reading a book, true fluency only comes from active practice. Cramming for 5 hours once a month is far less effective than practicing for 15 minutes every day.
Our platform is built on the principle of spaced repetition. By encountering a new problem daily, you reinforce neural pathways associated with database logic, syntax, and problem-solving. This ensures that when you face a high-pressure situation—like a technical interview or a critical production database fix—the correct syntax flows naturally.
Challenges are not random. They cycle through different difficulty levels (Easy, Medium, Hard) and topics. One day you might be asked to perform a simple `WHERE` filter, and the next you might need to construct a complex `Recursive CTE` to traverse a hierarchy.
We remove the friction of setting up a local database. No Docker containers, no `pip install` , no Postgres drivers. Our daily challenges run in a fully contained SQLite WASM sandbox within your browser, executing instantly and securely.
To become a complete SQL developer, you need to master more than just SELECT *. Our daily rotation covers the full spectrum of ANSI SQL and modern dialect features.
Beyond the basic INNER JOIN, you'll practice LEFT JOIN for finding missing records, FULL OUTER JOIN for complete report generation, and CROSS JOIN for generating combinations. We also cover UNION vs UNION ALL and EXCEPT for set mathematics.
Essential for data analysis. You'll learn to compute running totals with SUM() OVER, rank items with DENSE_RANK(), and compare current rows to previous ones using LEAD() and LAG(). These are heavily tested in interviews for Data Science roles.
Real-world data is messy. Challenges will require you to format dates (STRFTIME), handle NULL values with COALESCE, manipulate strings with SUBSTR and TRIM, and perform conditional logic using CASE WHEN statements.
Learn when to use a Common Table Expression (WITH clause) to make your code readable, versus a correlated subquery for specific filtering logic. We emphasize writing queries that are not just correct, but maintainable.
NULL is not equal to anything, not even itself. NULL = NULL returns NULL (falsey). You must use IS NULL.5 / 2 equals 2, not 2.5. You often need to cast to float: 5.0 / 2.SELECT clause that is not in the GROUP BY clause (and is not aggregated) is a common error that modern SQL engines reject.WHERE filters happen before aggregation, while HAVING filters happen after.Yes. You can browse previous daily SQL challenges from the history list and reopen earlier practice problems.
No account is required to practice. Progress is saved locally in your browser, and account-based sync is optional when available.
The daily challenge environment runs SQLite in the browser. Most concepts still transfer directly to PostgreSQL, MySQL, and SQL Server.
Our validtor checks both the data returned and the column names. Ensure your columns match the expected output exactly. Aliases are often required (e.g., SELECT count(*) AS total_users). Check the "Expected Result Columns" hint box.
Yes! We label challenges as Easy, Medium, or Hard. If you are brand new, we recommend starting with our Interactive Tutorials first to learn the basics, then coming here to practice.
Challenge Guide Available
This problem now has a dedicated evergreen detail page with solution approaches, common pitfalls, and FAQ content. Use Daily for repetition, or open the guide when you want the deeper explanation.
Write an SQL query to report the fraction of players that logged in again on the day after the day they first logged in, rounded to 2 decimal places.