Practice SQL That Actually Matters.In Microseconds.
Industry-grade analytical SQL challenges on isolated Parquet datasets. Evaluated by DuckDB in under 50ms. Guided by a Socratic AI Sensei that teaches you to think — not just solve.
| user_id | session_id | event_time |
|---|---|---|
| 1042 | 1 | 2026-08-16 09:12:00 |
| 1042 | 1 | 2026-08-16 09:25:30 |
| 1042 | 2 | 2026-08-16 10:45:10 |
What Makes KaizenCodes Different
Standard interview platforms run on slow shared databases. KaizenCodes embeds a columnar execution engine directly inside your browser and serverless edge.
Vectorized Execution
DuckDB on Parquet. Sub-50ms query evaluation, even on complex window frames, QUALIFY clauses, and multi-table joins.
Socratic AI Sensei
Reacts to your SQL AST and runtime errors. Guides you with two targeted questions — never spoils the solution.
Visual Query Profiler
Inspect physical plan trees, scan operators, filter pushdown, and memory metrics. Understand how databases actually execute.
Open Data Vault
Practice on authentic Cricket ball-by-ball, Stock tick data, and Government census sets. Free to practice, visualize, and download.
Curated Practice Tracks
Targeted pathways through the most critical analytical SQL patterns asked in top Data Engineering interviews.
Window Functions & Rankings
ROW_NUMBER, DENSE_RANK, LEAD/LAG, Running Totals & Sliding Frames.
Sessionization & Funnels
Inactivity time gaps, conversion funnel drops, and user session stitching.
Gaps & Islands Problems
Finding streaks, consecutive active dates, and contiguous range groups.
Multi-Join Analytics
Complex self-joins, anti-joins, full outer joins, and dimensional lookups.
CTE & Subquery Mastery
Modular query pipelines, recursive hierarchy traversals, and layered filters.
Query Optimization
Filter pushdown, partition pruning, and avoiding explosive cartesian joins.
Practice on Authentic, Real-World Datasets
Go beyond synthetic toy tables. KaizenCodes is building an open data ecosystem with authentic datasets formatted into high-performance Parquet files for direct querying, visualization, and open download.
| match_id | over | batter | bowler | runs_batter |
|---|---|---|---|---|
| 1426240 | 19.4 | MS Dhoni | H Pandya | 6 |
| 1426240 | 19.5 | MS Dhoni | H Pandya | 6 |
| 1426240 | 19.6 | MS Dhoni | H Pandya | 6 |
Your AI Mentor Never Gives You the Answer.
When you get stuck on a difficult query, copying and pasting the solution robs you of genuine intuition. AI Sensei inspects your current SQL attempt, the compiler error, and the dataset schema — replying with exactly two guiding questions to nudge your thinking.
“Struggle is the curriculum. Sensei is the guide.”
Output row count (14) does not match expected row count (10) due to duplicate ranks.
“Consider how RANK() handles ties compared to DENSE_RANK() or ROW_NUMBER(). When multiple employees share the exact same salary, which function guarantees strict deterministic ordering without gaps?”
Ready to Sharpen Your Data Engineering Edge?
Zero friction. No credit card required. Start querying and practicing immediately in the dojo.