Loading learning content...
Understanding DBMS concepts and succeeding in DBMS interviews are related but distinct skills. Many candidates read textbooks, watch tutorials, and feel prepared—only to stumble when facing live questions under pressure. The difference is deliberate practice: repeatedly solving problems, receiving feedback, and refining your approach.
This page provides a curated guide to the best resources for DBMS interview preparation. You'll learn where to practice SQL, how to study system design, which books are worth your time, and how to structure a preparation plan that maximizes results for your available time.
By the end of this page, you will have a curated list of SQL practice platforms, system design resources, textbooks and courses for deepening knowledge, mock interview options, and a framework for building your own personalized study plan.
SQL proficiency requires typing queries, debugging syntax, and getting hands-on feedback—not just reading examples. These platforms provide interactive SQL environments with structured problem sets:
| Platform | Strengths | Best For | Cost |
|---|---|---|---|
| LeetCode (Database) | Interview-focused problems; company tags; discussion forums | Interview preparation; pattern recognition | Free tier + Premium ($35/mo) |
| HackerRank (SQL) | Skill certifications; progressive difficulty; clear problem statements | Beginners to intermediate; portfolio building | Free tier + Pro |
| DataLemur | Real company interview questions; SQL explanations; curated content | Targeted interview prep; seeing actual questions | Free tier + Premium |
| StrataScratch | Company-specific questions; data science focus; multiple SQL dialects | Data roles; tech-specific preparation | Free tier + Premium |
| SQLZoo | Tutorial-style progression; excellent for learning; concept-based | Learning SQL fundamentals; beginners | Free |
| Mode Analytics SQL Tutorial | Business context problems; analytics-focused; real datasets | Analysts; business intelligence roles | Free |
| PostgreSQL Exercises (pgexercises.com) | PostgreSQL specific; joins, aggregates, CTEs focus | PostgreSQL proficiency; concept mastery | Free |
| Codewars | Gamified learning; community solutions; multiple languages including SQL | Variety; competitive motivation | Free |
How to Use SQL Platforms Effectively:
Solving 500 easy problems teaches less than deeply understanding 50 medium problems. After solving a problem, ask: "Could I explain this to someone else? Could I solve a variant?" If not, study the solution until you could.
Schema design and database architecture questions require understanding principles that aren't easily learned through problem sets alone. These resources build the conceptual foundation and practical intuition needed for design interviews:
If targeting senior or staff-level roles, prioritize "Designing Data-Intensive Applications" and the CMU Database Course. These provide the depth that separates senior candidates from mid-level. Junior candidates can focus on more foundational resources first.
Theoretical knowledge—normalization theory, transaction isolation, concurrency control—is best learned from structured explanations and repeated study. These resources cover essential concepts:
| Resource Type | Recommended Resources | Content Focus |
|---|---|---|
| Textbooks | "Database System Concepts" (Silberschatz), "Fundamentals of Database Systems" (Elmasri/Navathe) | Comprehensive coverage of theory; normalization, ER modeling, transactions, recovery |
| Quick Reference | Use-The-Index-Luke.com, PostgreSQL/MySQL documentation | Indexing deep dives; official documentation for syntax and behavior |
| Interview Prep Guides | InterviewBit Database section, GeeksforGeeks DBMS tutorials | Question-oriented learning; common interview topics explained |
| Flashcard Systems | Anki (create your own), Quizlet (search for DBMS decks) | Spaced repetition for memorizing definitions and key concepts |
| Blogs/Articles | Percona Database Blog, PostgreSQL Wiki, AWS Database Blog | Real-world insights; production experiences; new developments |
| Podcasts | Data Engineering Podcast, Postgres FM | Stay current; learn from practitioners; background learning |
Create a personal reference document covering key concepts: isolation levels, normal forms, index types, join algorithms. Reviewing your own condensed notes is more effective than re-reading textbooks. Update it as you learn.
Solo practice has limits. Real interview pressure, articulating answers aloud, and receiving external feedback reveal gaps that self-study misses. Mock interviews bridge this gap:
Getting Maximum Value from Mock Interviews:
| Before | During | After |
|---|---|---|
| Request specific question types (SQL, design, conceptual) | Treat it like a real interview—no looking things up | Ask for specific feedback: "What could I improve?" |
| Prepare environment: quiet space, stable connection, notepad | Think aloud; communicate as you would in real interview | Take notes on feedback immediately |
| Set clear time limits for each question type | If stuck, say so and ask for hints—practice that skill too | Identify 2-3 specific takeaways to work on |
| Review relevant concepts beforehand | Mind your pacing—don't rush or drag | Schedule your next mock to practice improvements |
Many candidates practice problems but skip mocks due to social discomfort. This is a mistake. The difference between solving problems alone and explaining solutions under pressure is enormous. Treat mocks as essential, not optional. Aim for at least 5-10 mock interviews before a target interview.
Beyond online platforms, having a local database environment allows unrestricted experimentation—loading datasets, testing queries, breaking things safely. This hands-on practice builds intuition that platforms can't.
docker run -e POSTGRES_PASSWORD=pass -p 5432:5432 postgres12345678910111213141516171819202122
# Quick PostgreSQL setup with Docker # 1. Start PostgreSQL containerdocker run --name pg-practice -d \ -e POSTGRES_USER=practice \ -e POSTGRES_PASSWORD=practice \ -e POSTGRES_DB=interview_prep \ -p 5432:5432 \ postgres:15 # 2. Connect with psqldocker exec -it pg-practice psql -U practice -d interview_prep # 3. Or use any GUI tool (DBeaver, pgAdmin, DataGrip) connecting to localhost:5432 # 4. Load sample data (example: Pagila - PostgreSQL sample database)# Download from: https://github.com/devrimgunduz/pagila# Or: https://www.postgresqltutorial.com/postgresql-sample-database/ # 5. To reset everything: docker stop pg-practice && docker rm pg-practice# Then run step 1 again for a fresh databaseRecommended Sample Datasets for Practice:
| Dataset | Description | Good For Practicing |
|---|---|---|
| Pagila (PostgreSQL) | DVD rental store data—customers, films, rentals, staff | Joins, aggregations, CTEs, window functions |
| Sakila (MySQL) | Same as Pagila but for MySQL | MySQL-specific syntax and features |
| Chinook | Digital music store—artists, albums, tracks, invoices | Multi-table joins, analytics queries |
| Northwind | Classic Microsoft sample—orders, products, customers | Business analytics, reporting queries |
| AdventureWorks (SQL Server) | Large, complex enterprise sample—HR, sales, production | Complex schemas, enterprise patterns |
| StackOverflow Data Dump | Real StackOverflow data—very large | Scaling, performance tuning, real data quirks |
Design and build schemas for systems you understand: a simple e-commerce site, a social media feed, a booking system. Writing the CREATE TABLE statements and INSERT data yourself reinforces design thinking in ways that using premade datasets doesn't.
Having resources is useless without a plan to use them. Here are time-boxed study plans for different preparation timelines. Adapt based on your current level and target role.
For: Candidates with solid fundamentals who need to sharpen and practice
Week 1: Refresh and Practice
Week 2: Simulate and Polish
These plans are templates, not prescriptions. If you're strong in SQL but weak on design, shift time accordingly. If you've been interviewing and know specific weak areas, prioritize those. The best plan is the one you'll actually follow consistently.
Systematic tracking helps you focus effort where it's most needed and build confidence through visible progress. Here's how to track effectively:
# DBMS Interview Prep Tracker ## Problems Log| Date | Problem | Platform | Topic | Difficulty | Time | Hints? | Notes ||------|---------|----------|-------|------------|------|--------|-------|| 1/15 | Top-N per dept | LeetCode | Window Functions | Medium | 18 min | No | Used DENSE_RANK || 1/15 | Running total | DataLemur | Window Functions | Medium | 12 min | No | SUM() OVER(ORDER BY) || 1/16 | Consecutive days | LeetCode | Gap & Island | Hard | 35 min | Yes | Need more practice here | ## Weekly Confidence Ratings (1-5)| Week | SQL Joins | Window Func | Normalization | Indexing | Transactions | Design ||------|-----------|-------------|---------------|----------|--------------|--------|| 1 | 3 | 2 | 4 | 3 | 3 | 2 || 2 | 4 | 3 | 4 | 4 | 3 | 3 || 3 | 4 | 4 | 5 | 4 | 4 | 3 | ## Mock Interview Log| Date | Interviewer | Focus | Strengths | Improve ||------|-------------|-------|-----------|---------|| 1/20 | Pramp peer | SQL | Clear communication | Speed on window functions || 1/25 | Colleague | Design | Good requirements gathering | Discuss indexes earlier | ## Identified Gaps (Prioritize These)- [ ] Recursive CTEs - need more practice- [ ] Gap and island problems- [ ] MVCC internals explanation- [ ] Sharding key selection rationaleEvery Sunday, spend 20 minutes reviewing your tracking data. What topics saw improvement? Where are persistent gaps? Adjust next week's plan based on data, not just feelings. This deliberate reflection accelerates progress.
Interview preparation is more sustainable and effective with community support. These resources connect you with others on the same journey:
| Platform | Type | Best For |
|---|---|---|
| r/cscareerquestions | Reddit community | General interview prep discussion, experience sharing |
| r/learnSQL | Reddit community | SQL-specific questions and resources |
| Blind | Anonymous professional network | Company-specific interview experiences, salary data |
| Database Discord servers | Real-time chat | Quick questions, study groups, community support |
| Tech Twitter/X | Social media | Following database experts, industry trends |
| Local Meetups | In-person events | Networking, finding study partners, local job market insight |
| LeetCode Discuss | Problem forums | Solution explanations, company-specific tags |
Interview preparation skills translate directly into on-the-job excellence. The systematic learning, practice, and self-assessment habits you build here serve you throughout your career. View preparation as building permanent capabilities, not just passing a hurdle.
You now have a comprehensive map of resources for DBMS interview preparation. Let's consolidate the key points:
What's Next:
Resources and practice build skills; career strategy deploys them. The final page explores career guidance—how to position your DBMS expertise for different roles, navigate the job market, and continue growing professionally.
You now have a complete resource toolkit for DBMS interview preparation. The difference between candidates who succeed and those who don't often comes down to consistent, structured practice over weeks—not raw talent. Use these resources wisely, and you'll be prepared for any DBMS interview challenge.