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Lyft·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Lyft software engineer coding round, laptop-based, 1.5 hours to build an in-memory key-value store with transaction support. Time was tight and I did not get it fully bug-free.

Questions Asked (1)

Q1

Build an in-memory key-value database that supports begin, commit, and rollback for transactions.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

Ran out of time before I had a clean solution.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a design using a stack of transaction layers where each layer maintains a map of key-value changes. Explain how begin pushes a new layer, commit merges the top layer into the one below, and rollback discards the top layer. Discuss trade-offs between simplicity and performance, and consider edge cases like nested transactions and read-your-writes consistency.

Pro tip: Demonstrate awareness of real-world database semantics by discussing isolation levels and how your in-memory design could be extended to support them, showing you think beyond the basic implementation.

1. Clarify Requirements and Constraints

Ask about expected operations (get, set, delete), transaction nesting, concurrency, and performance requirements. Confirm whether reads should see uncommitted changes within the same transaction.

2. Design Core Data Structures

Propose a stack of transaction layers, each containing a hash map for key-value changes. The base layer holds committed data, and each begin pushes a new layer.

3. Define Transaction Operations

Explain how begin creates a new layer, commit merges the top layer into the previous one (handling conflicts), and rollback simply pops the top layer.

4. Handle Reads and Writes

Describe how get searches from the top layer down to the base, and set/delete write to the top layer. Mention read-your-writes consistency within a transaction.

5. Discuss Trade-offs and Extensions

Talk about time/space complexity, alternatives like copy-on-write or undo logs, and how to extend for concurrency, isolation levels, or persistence.

Key Points to Mention

  • Use a stack of transaction layers (maps) to support nested transactions.
  • Commit merges changes upward; rollback discards the top layer.
  • Reads traverse layers from top to bottom to ensure read-your-writes.
  • Time complexity: O(1) for begin/commit/rollback (amortized), O(depth) for reads.
  • Space complexity: O(total uncommitted changes) across layers.
  • Trade-offs: simplicity vs. performance, memory overhead, and concurrency handling.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.