Google vs Airbnb: Interview Question Comparison

When preparing for technical interviews, understanding company-specific patterns is crucial. Both Google and Airbnb are top-tier tech companies, but their interview approaches differ significantly in scale and focus. This comparison breaks down the key differences in question volume, difficulty, and topic emphasis to help you strategize your preparation.

Question Volume and Difficulty

The most striking difference is the sheer volume of available practice questions. Google's dataset is massive, with 2,217 questions categorized by difficulty (Easy: 588, Medium: 1,153, Hard: 476). This reflects Google's vast interview history and the wide variety of problems candidates might encounter. You should expect a strong emphasis on problem-solving fundamentals applied in novel ways, with a significant portion of questions being Medium or Hard difficulty.

In contrast, Airbnb's dataset is much smaller, with 64 questions (Easy: 11, Medium: 34, Hard: 19). This doesn't mean Airbnb interviews are easier; it indicates a more curated and possibly more consistent question bank. The difficulty distribution is similarly weighted toward Medium and Hard problems, suggesting a comparable bar for technical proficiency, but within a narrower scope of problem types.

Key Takeaway: Preparing for Google requires broader exposure to a vast array of problems. Preparing for Airbnb requires deep, focused practice on a smaller set of problem patterns, where mastering each one is critical.

Topic Overlap

Both companies emphasize core data structures and algorithms. The top four topics for both are identical:

• Array
• String
• Hash Table
• Dynamic Programming

This overlap means a strong foundation in these areas is non-negotiable for either company. You must be proficient in manipulating arrays and strings, using hash maps for efficient lookups, and applying dynamic programming to optimization problems.

The difference lies in the context and application. Google's enormous question pool will test these fundamentals across a dizzying variety of scenarios, often combining multiple concepts in a single problem. Airbnb's questions, while grounded in the same topics, may be more directly tied to real-world scenarios relevant to their business domain, such as reservations, scheduling, or matching.

Coding Example: A classic "Two Sum" problem (Hash Table)

def two_sum(nums, target):
    seen = {}
    for i, num in enumerate(nums):
        complement = target - num
        if complement in seen:
            return [seen[complement], i]
        seen[num] = i
    return []

Which to Prepare for First

Start with Google.

Preparing for Google's interview builds a comprehensive and robust foundation. The vast number of Medium-difficulty questions forces you to become adept at recognizing patterns, optimizing solutions, and handling edge cases across countless problem types. This deep, wide practice will make you over-prepared for the narrower, yet still challenging, scope of Airbnb's questions. The core topics are the same, so your effort transfers directly.

If you are interviewing at Airbnb specifically, use the Google-focused preparation as your baseline. Once comfortable, shift to a targeted review of Airbnb's question list. Practice these problems meticulously to understand the specific nuances and potential real-world twists the company favors. The goal is to transform your broad competency into focused excellence on their known problem set.

In short, Google prep builds the universal engine; Airbnb prep fine-tunes it for a specific vehicle.

For focused practice, visit the company pages: Google and Airbnb.