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System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master system design interviews.

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This is a hard difficulty System Design question, commonly asked during Technical Screen rounds at OpenAI.

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

Design an in-memory database | OpenAI Interview Question

Quick Overview

This question evaluates understanding of in-memory database engine design, including data model and API surface, in-memory storage layout and indexing, query execution, transaction isolation and concurrency control, durability mechanisms (WAL, snapshots, recovery), and strategies for replication and sharding.

System Design: In-Memory Database Engine (Single-Node Core, Scale-Out Aware)

Context

Design the core of an in-memory, single-node database engine intended to be the building block for a larger distributed system. Data is primarily memory-resident on each node; durability and scale-out are achieved via logging, snapshots, and replication/sharding across multiple such nodes.

Requirements

CRUD operations on records.
Efficient querying: point lookups and range scans; basic filtering and ordering.
Transaction isolation: define levels supported (at least read committed and snapshot isolation; discuss path to serializable).
Persistence and backup: crash recovery, snapshots/checkpoints, WAL, and restore.
Horizontal scalability: strategy for replication and sharding across multiple single-node instances.

Deliverable

Provide a design that covers:

Data model and API surface.
In-memory storage layout and indexing.
Query execution approach.
Concurrency control and transaction management.
Durability: WAL, checkpoints/snapshots, recovery.
Backup/restore strategy.
Horizontal scaling: replication and sharding.
Operational concerns: garbage collection, observability, and pitfalls.

Quick Overview

Requirements

CRUD operations on records.

Efficient querying: point lookups and range scans; basic filtering and ordering.

Transaction isolation: define levels supported (at least read committed and snapshot isolation; discuss path to serializable).

Persistence and backup: crash recovery, snapshots/checkpoints, WAL, and restore.

Horizontal scalability: strategy for replication and sharding across multiple single-node instances.

Deliverable

Provide a design that covers:

Data model and API surface.

In-memory storage layout and indexing.

Query execution approach.

Concurrency control and transaction management.

Durability: WAL, checkpoints/snapshots, recovery.

Backup/restore strategy.

Horizontal scaling: replication and sharding.

Operational concerns: garbage collection, observability, and pitfalls.

Design an in-memory database

Quick Overview

System Design: In-Memory Database Engine (Single-Node Core, Scale-Out Aware)

Context

Requirements

Deliverable

Solution

Submit Your Answer to Earn 20XP

Design an in-memory database

Quick Overview

System Design: In-Memory Database Engine (Single-Node Core, Scale-Out Aware)

Context

Requirements

Deliverable

Solution

Submit Your Answer to Earn 20XP