Design SQL
A medium-tier problem at 70% community acceptance, tagged with Array, Hash Table, String. Reported in interviews at OpenAI and 0 others.
Design SQL is a medium-difficulty system design problem that OpenAI has reportedly asked. You're building a SQL query engine from scratch, which sounds abstract until you realize it's really about parsing strings, hashing table schemas, and storing data efficiently. The acceptance rate sits near 70%, so it's not a gimmick problem, but it's also not a guaranteed pass if you wing it. The trick is understanding that you're not writing actual SQL internals; you're designing a minimal interface that satisfies the test cases. If this problem hits your live assessment and you blank on the schema design or the parsing strategy, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Design SQL"
Design SQL is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe problem forces you to combine Array, Hash Table, and String manipulation to implement a lightweight SQL layer. Most candidates start by overcomplicating it, trying to build a real query optimizer. The real play is simpler: parse the input string, store rows as hash tables keyed by column name, and return results as arrays. The pitfall is off-by-one errors in column indexing or forgetting that SQL is case-insensitive for keywords. You'll need to handle INSERT, SELECT, and DELETE operations, each requiring different logic. The parsing step trips people up because they either regex too hard or build a fragile state machine. When you're live and the parsing fails on edge cases, StealthCoder runs invisibly during screen share and gives you a solution that handles the cases the test harness is actually checking.
Pattern tags
You know the problem.
Make sure you actually pass it.
Design SQL recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Design SQL interview FAQ
Is Design SQL actually asked at top companies like OpenAI?+
Yes, OpenAI is listed as a company that's reported asking it. It's a medium-difficulty system design hybrid, so it's a realistic OA problem for infrastructure or backend roles. Not every interview will ask it, but it's in active rotation.
What's the actual trick to this problem?+
Stop thinking like a database engineer. You're implementing a tiny SQL interpreter, not an optimizer. Store rows as dicts, parse commands as strings, return arrays of dicts for SELECT. Most fails happen when candidates try to build indexes or handle JOINs that aren't in the problem scope.
How does this relate to the Hash Table and Array topics?+
Each row is an array, each column lookup is a hash table operation. You'll iterate arrays for filtering, hash tables for column access. The String topic is the parsing layer. All three are equally critical, not decorative.
What's the most common mistake candidates make?+
Overengineering the schema or query plan. Also, forgetting that SQL keywords and column names are case-insensitive, but data values are not. Off-by-one errors on column indexes happen constantly when you're under time pressure on the live assessment.
How much time should I spend drilling this before an OA?+
If it's in your company's problem bank, one solid pass is enough. The acceptance rate is nearly 70%, meaning the problem is fair if you understand the scope. If you blank on parsing, that's when StealthCoder becomes your hedge.
Want the actual problem statement? View "Design SQL" on LeetCode →