Is this a video course?

No. This is an interactive, slide-based learning platform. Each lesson has rich text, animated diagrams, live code editors, and quizzes. You learn by reading, interacting, and doing, not by watching videos passively.

How long do I have access?

Forever. Both pricing tiers are one-time payments with lifetime access. This includes all current 766 lessons and any future content we add.

What level of experience do I need?

None. We start from absolute basics like 'What is latency?' and build up to distributed consensus protocols. The Foundation level assumes zero prior knowledge of system design.

How much does the system design course cost?

7.99 US dollars for lifetime access globally, or 499 Indian rupees for lifetime access in India. One-time payment, no subscription, no hidden fees. 11 lessons are free with no signup required.

What technologies are covered?

Everything from DNS and load balancers to Kubernetes, Kafka, distributed databases, consensus protocols, stream processing, security architecture, and observability. We cover principles and real-world implementations used at Netflix, Google, Amazon, Uber, Stripe, and more.

Is this useful for system design interview preparation?

Yes. The lessons are structured around the exact topics asked in system design interviews at FAANG and top-tier companies. Interactive diagrams help you practice whiteboard-style explanations. Covers everything from URL shortener design to distributed payment systems.

How is this different from ByteByteGo or Educative?

766 interactive lessons (4x more than most competitors), 16 different diagram types that build step by step, real production examples from Netflix, Google, Amazon, Uber, and Stripe, and lifetime access for a one-time payment of $7.99 instead of annual subscriptions costing 100 to 200 dollars per year.

What's the key difference between database buffer pool caching and result set caching?

Buffer pool caches raw data pages; result set caching caches the final query output, The buffer pool caches raw data pages (the 8-16 KB blocks stored on disk). The database still has to join, filter, and sort those pages for every query. Result set caching stores the final, assembled result, the exact rows your application needs, skipping all that work on cache hits.

Your cache TTL expires and 500 concurrent users all trigger the same expensive query. What is this problem called?

Cache stampede (thundering herd), A cache stampede (or thundering herd) happens when a popular cache entry expires and many concurrent requests all experience a cache miss simultaneously, flooding the database with the same expensive query. Solutions include locking (only one fetches while others wait) and stale-while-revalidate.

When is a Postgres materialized view a better choice than caching result sets in Redis?

When the result needs to be queryable and indexable like a regular table, Materialized views are stored as physical tables, you can create indexes on them, join them with other tables, and query them with WHERE clauses. Redis just gives you a blob. If you need to further filter or join cached results, a materialized view is the right tool.

Result Set Caching

Name: System Design Masterclass
Availability: InStock

in Caching Strategies

This lesson is part of the full System Design Masterclass. Unlock it along with 765 other lessons for a one-time payment.

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Foundation lessons free, try before you buy

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India

₹999₹499/lifetime

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Foundation lessons free, try before you buy

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“The interactive diagrams alone are worth way more than the price.”

Anish K., Senior Engineer at a Bengaluru startup

All 766 interactive lessons

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