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SQL Interview Practice Challenges

Ranking updated Jun 30, 2026

For a practice set for SQL interviews, the strongest matches are youssefhosni/data-science-interview-questions-answers (This repository is a static collection of data science), lerocha/chinook-database (Chinook is a sample database of a fictional media) and enochtangg/quick-sql-cheatsheet (This is a static SQL syntax reference and cheat). haoel/leetcode and enhorse/java-interview round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.

Practice complex database queries and technical interview problems to sharpen your SQL development and analytical skills.

SQL Interview Practice Challenges

Find the best repos with AI.We'll search the best matching repositories with AI.
  • youssefhosni/data-science-interview-questions-answersyoussefHosni avatar

    youssefHosni/Data-Science-Interview-Questions-Answers

    5,497View on GitHub↗

    This repository is a curated study resource of interview questions and answers for data science roles. It covers the core domains of machine learning, statistics, Python programming, SQL databases, deep learning, and algorithmic problem solving. The content is organized as static Markdown files with a structured question-and-answer format, making it easy to read and navigate without any server-side processing. The material distinguishes itself by pairing each question with a detailed explanation and often a code example, covering both conceptual knowledge and practical application. Topics ran

    This repository is a static collection of data science interview Q&A covering SQL among other topics, so it includes SQL practice questions but is not a dedicated interactive platform with a query editor or real datasets.

    SQL Interview QuestionsSQL Questions
    View on GitHub↗5,497
  • lerocha/chinook-databaselerocha avatar

    lerocha/chinook-database

    2,544View on GitHub↗

    This project is a relational SQL sample database and synthetic testing dataset. It provides a standardized data model of a fictional digital media store, encompassing business entities such as artists, albums, tracks, customers, and invoices. The dataset is designed as a cross-dialect SQL collection, using compatible scripts to ensure consistent data seeding and environment parity across different database server engines. It combines imported metadata with fictitious personal details to create realistic records for software prototyping and demonstrations. The project covers capabilities for

    Chinook is a sample database of a fictional media store, useful for practicing SQL queries, but it lacks the interview-style problems, interactive editor, and solution explanations you're looking for.

    TSQLSQL Sample Databases
    View on GitHub↗2,544
  • enochtangg/quick-sql-cheatsheetenochtangg avatar

    enochtangg/quick-SQL-cheatsheet

    5,406View on GitHub↗

    This project is a relational database cheat sheet and SQL reference guide. It provides a collection of syntax examples and query documentation for managing relational databases using structured query language. The tool is implemented as a static site with client-side searchable documentation, allowing for immediate filtering of technical content through a browser-based index. The reference covers relational database management, including data retrieval, database schema management, and record maintenance. It also includes guidance on relational data manipulation through table joins and the g

    This is a static SQL syntax reference and cheat sheet, not a collection of interview-style practice problems with an interactive query editor and solution explanations, so it does not directly match the search for a query challenge platform.

    Group-By AggregationsSQL Aggregate Functions
    View on GitHub↗5,406
  • haoel/leetcodehaoel avatar

    haoel/leetcode

    18,058View on GitHub↗

    This project is a library of source code implementations designed to solve algorithmic challenges and mathematical problems. It serves as a collection of solved LeetCode problems, providing a reference for data structure usage and efficient logic. The repository is a polyglot code collection, implementing the same algorithmic logic across various programming environments, including general-purpose languages, SQL for database queries, and Bash for shell scripting. The content covers a broad range of computational tasks, including data querying, text processing, and the implementation of compl

    This repository is a collection of solved LeetCode problems including SQL queries, offering solutions to interview-style questions, but it does not provide an interactive query editor or structured practice exercises as requested.

    C++SQL Challenge Solutions
    View on GitHub↗18,058
  • enhorse/java-interviewenhorse avatar

    enhorse/java-interview

    6,036View on GitHub↗

    This is a structured collection of interview preparation materials organized as a question bank covering multiple technology domains. The content is stored as plain Markdown files arranged in a topic-based directory hierarchy, delivered as static HTML without any JavaScript framework or build pipeline. The material focuses on Java ecosystem topics including core language features, collections, multithreading, JVM internals, Java 8 features, I/O, serialization, OOP principles, JDBC, servlets and JSP, logging, reactive programming, and testing. It also covers relational databases and SQL, web d

    This repo is a broad interview-preparation question bank that includes some SQL questions in static Markdown files, but it lacks an interactive query editor or executable examples, so it's not a dedicated SQL practice platform with the hands-on exercise environment this search asks for.

    BatchfileSQL Questions
    View on GitHub↗6,036
  • dbcli/pgclidbcli avatar

    dbcli/pgcli

    13,231View on GitHub↗

    pgcli is an interactive command-line interface and database management tool for PostgreSQL. It functions as an interactive SQL shell and query editor that allows users to inspect schemas, manage connections, and run queries against PostgreSQL data sources. The tool is distinguished by its real-time, schema-aware autocompletion for keywords, tables, and columns, as well as dynamic SQL syntax highlighting. It provides safety mechanisms through transaction-aware guardrails that warn against or block destructive statements when no active transaction is detected. Broad capabilities include secure

    pgcli is an interactive SQL shell and query editor for PostgreSQL, not a collection of interview-style practice problems with solutions and real datasets.

    PythonInteractive Data Querying Tools
    View on GitHub↗13,231
  • datacharmer/test_dbdatacharmer avatar

    datacharmer/test_db

    4,388View on GitHub↗

    test_db is a collection of tools for validating database integrity, benchmarking system throughput, and generating synthetic schemas and datasets. It includes a sample corporate employee database for MySQL, a SQL dataset generator for creating representative records, and an integrity validator that uses checksums and record counts to verify data consistency across different database engines. The project provides a database performance benchmark consisting of complex queries and stored procedures designed to measure system response times and throughput. These tools simulate real-world workload

    This repository provides a sample employee database and benchmark queries for performance testing, not a structured set of interview-style SQL practice problems with solutions and varying difficulty levels.

    ShellSample Datasets
    View on GitHub↗4,388
  • querydsl/querydslquerydsl avatar

    querydsl/querydsl

    4,964View on GitHub↗

    Querydsl is a framework for the construction of type-safe queries. It uses a fluent API and annotation-based code generation to create mirror classes from domain models, enabling compile-time validation of database queries and removing the need for manual string concatenation. The project provides a unified query syntax that translates into specific dialects for multiple backends, including SQL, MongoDB, Lucene, and JDO. It supports advanced query capabilities such as common table expressions, window functions, geospatial operations, and complex nested subqueries. Beyond data retrieval, the

    Querydsl is a type-safe query construction framework for Java, not a collection of SQL interview practice problems — it helps developers build queries programmatically, but does not provide hands-on exercises, solutions, or realistic interview questions.

    JavaSubquery SupportWindow Functions
    View on GitHub↗4,964

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