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This question is commonly asked for Software Engineer candidates at OpenAI during technical interviews.

Design in-memory database API | OpenAI Interview Question

Q: Design in-memory database API

This question evaluates a candidate's ability to design and reason about in-memory data storage, indexing, query planning, and the underlying data structures and algorithms for insert and query operations.

In-Memory Database: Insert, Query, and Indexing

Context

You are to design a minimal, single-process, in-memory database to be embedded in a service. The database manages multiple named tables with simple schemas and must support:

write: insert(table, record)
read: query(table, columns_to_project, conditions=[(column, operator, value)], order_by=(columns, ascending))

Assume:

Records are dictionaries keyed by column name.
Each table has a defined schema (column names and basic types like int/float/string), but you may keep type handling simple.
Operators include: =, !=, <, <=, >, >=, IN (optional). Combine conditions with AND semantics.
order_by takes one or more columns and a boolean ascending flag.
Single-threaded execution is fine; you do not need transactions or persistence.

Tasks

Design the in-memory data structures and algorithms to implement insert and query.
Provide an implementation sketch (pseudocode or a compact, idiomatic language like Python/Go/Java) showing the core logic.
Extend the design to explain how indexes would be built and used to speed up WHERE (conditions) and ORDER BY queries, including:
- What index types you would support and why.
- How inserts update indexes.
- How the query planner chooses which index to use for different predicates and orderings.
- Complexity trade-offs and edge cases.

Context

You are to design a minimal, single-process, in-memory database to be embedded in a service. The database manages multiple named tables with simple schemas and must support:

write: insert(table, record)

read: query(table, columns_to_project, conditions=[(column, operator, value)], order_by=(columns, ascending))

Assume:

Records are dictionaries keyed by column name.

Each table has a defined schema (column names and basic types like int/float/string), but you may keep type handling simple.

Operators include: =, !=, <, <=, >, >=, IN (optional). Combine conditions with AND semantics.

order_by takes one or more columns and a boolean ascending flag.

Single-threaded execution is fine; you do not need transactions or persistence.

Tasks

Design the in-memory data structures and algorithms to implement insert and query.

Provide an implementation sketch (pseudocode or a compact, idiomatic language like Python/Go/Java) showing the core logic.

Extend the design to explain how indexes would be built and used to speed up WHERE (conditions) and ORDER BY queries, including:

What index types you would support and why.
How inserts update indexes.
How the query planner chooses which index to use for different predicates and orderings.
Complexity trade-offs and edge cases.

Design in-memory database API

Quick Overview

In-Memory Database: Insert, Query, and Indexing

Context

Tasks

Solution

Comments (0)

Design in-memory database API

Quick Overview

In-Memory Database: Insert, Query, and Indexing

Context

Tasks

Solution

Comments (0)