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Stop memorizing, start pattern matching
By Evan King
Mar 6, 2025
The difference between passing and failing your system design interview often comes down to one thing: whether you've memorized solutions, or truly understand them.
Imagine you're in a system design interview. The interviewer asks you to design a system for tracking driver locations for a ride-sharing app. Your mind races, you remember seeing something about Redis and geohashing… and you confidently throw it out there: "We should use Redis with geohashing!" Then the interviewer asks, "Great! Can you explain why?" And suddenly, you freeze. You've fallen into a trap of memorization. You've recalled the what but not the why.
Memorization is simply recalling facts or solutions without understanding them. In an interview, it's reciting "Redis with geohashing" without understanding why that might be a good or bad choice for this specific problem.
You're setting yourself up to have egg on your face with even the gentlest of probes from your interviewer.
Pattern matching, on the other hand, is an entirely different cognitive skill - one that transforms how you approach system design. It's the ability to map a known set of solutions to a given problem, and, crucially, understanding how and why those solutions work. It's not just remembering "Redis"; it's understanding the characteristics of in-memory data stores (high read throughput, low latency) and recognizing when they are appropriate. It's recognizing the common need for geospatial indexing in location-based services and understanding the trade-offs between different indexing techniques (geohashing, quadtrees, etc.). It's about having a mental toolkit of proven solutions and knowing how to apply them effectively.
Memorization is shallow; pattern matching is deep. One gives you the illusion of knowledge; the other empowers you to solve problems.
I know what you're thinking: "Easier said than done." I get it. There's no magic bullet, no shortcut to mastery. It takes hard work.
Here are some strategies that we've observed work for successful candidates.
Preparation:
- Deconstruct, don't just consume: Don't just passively read articles or watch videos. Actively engage with the material. Try to recreate designs, solve problems on your own, and question assumptions. We have dozens of breakdowns of common system design questions at www.hellointerview.com. Before you read them, try to design the system yourself.
- Force yourself to struggle: Resist the urge to immediately look up the answer the second you're stuck. Struggling with a problem is often the best way to learn. I promise you you'll retain 10x the amount of information after you struggle with it. The discomfort will help it stick.
- Gain as much exposure to as many problems as is reasonable in your timeframe: The more problems you see, the more patterns you'll recognize. Try to design a couple of systems a day. Realistically, there are only a few dozen popular system design questions. In only a couple of weeks, you can have thorough exposure to each of them.
- Connect the dots: Be inquisitive. When something doesn't make sense, actively seek answers. Use ChatGPT, Google, or other resources to deepen your understanding. The goal is to build a web of interconnected knowledge, not just a collection of isolated facts.
During the Interview:
- Start with the problem: Instead of immediately jumping to solutions you remember, articulate the core problem being solved. For the driver location example, don't say "Redis with geohashing." Instead, say: "We need to track the real-time location of a large number of drivers (e.g., hundreds of thousands) and efficiently query for nearby drivers, all while handling a high volume of location updates." This immediately shifts the focus to the why and sets the stage for reasoned pattern matching.
- Then, pattern match (with multiple options): After clearly defining the problem, you can leverage your knowledge of common patterns. "Given these requirements, we might consider several different approaches. One option is to use an in-memory data store like Redis, which is well-suited for high write throughput and low latency. Another option could be PostGIS, which provides robust spatial queries. A third option, particularly if we needed extreme control over performance, might be a custom in-memory quadtree implementation." Notice how the pattern matching is now directly tied to the specific requirements of the problem and presents multiple options.
- Weigh tradeoffs: This is what the interviewer really wants to see. It's not that you remember a pattern, but that you know why it's right for the given problem relative to other solutions that might exist. "Redis is excellent for high write throughput, which is essential for handling frequent location updates. However, it has limitations in terms of data persistence and complex spatial queries. PostGIS, while offering powerful spatial querying, might become a bottleneck at high write volumes, potentially requiring complex sharding. A custom quadtree offers the most control but requires significant development and maintenance overhead. For this use case, where write throughput and simple radius queries are key, Redis seems like the most appropriate starting point." This shows the interviewer you've considered multiple options and rationally chosen one based on the specific constraints.
To jumpstart your pattern-matching toolkit, here is a small set of powerful patterns and the problems they elegantly solve
| Problem | Potential Solutions | Common Problems |
|---|---|---|
| Efficiently finding locations within a radius | Geospatial indexes (e.g., geohashing, quadtrees, R-trees) supported by technologies like PostGIS, Elasticsearch, Redis. | Uber, Tinder, Yelp |
| Efficient full-text search over large datasets | Inverted indexes (e.g., Postgres full-text search, Elasticsearch) | Yelp, Ticketmaster |
| Pessimistically locking resources for extended periods | Distributed locks with Time-To-Live (TTL) | Ticketmaster, Uber |
| Database consistency during high concurrency | Transactions with row locking or Optimistic Concurrency Control (OCC) | Yelp, Online Auction |
| High write throughput with low latency | In-memory data stores (e.g., Redis, Memcached) | Bit.ly, Ad click aggregators |
| Isolation when concerned about running external code | Containers | LeetCode |
| Broadcasting messages to users in real-time | Pub/sub with SSE or WebSockets | Facebook Live Comments, WhatsApp |
| Uploading or downloading large files | Chunking | YouTube, Dropbox |
System design interviews aren't about memorizing a playbook of perfect answers - they're about developing the intuition to recognize patterns and apply them thoughtfully. Think of it like learning to cook: a beginner follows recipes blindly, while a chef understands why certain ingredients work together and can adapt on the fly. Stop memorizing solutions, start understanding patterns, and you'll find yourself not just passing interviews, but becoming a better engineer.
About The Author
Evan, Co-founder of Hello Interview and former Staff engineer at Meta, possesses a unique vantage point having been on both sides of the tech hiring process. With a track record of conducting hundreds of interviews and securing offers from top tech companies himself, he is now on a mission to help others do the same.
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