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.

How do column-family stores differ from columnar databases like BigQuery?

Column-family stores group dynamic columns per row for flexible schemas, while columnar databases store each column separately for analytical scans, Despite the similar names, they solve different problems. Column-family stores (Cassandra, HBase) offer flexible per-row columns for operational workloads. Columnar databases (BigQuery, Redshift) physically store each column separately for fast analytical scans.

Why is row key design the most critical decision in a column-family store?

Data is distributed and retrieved by row key, queries without the row key are inefficient or impossible, Column-family stores distribute data across nodes based on the row key and require it for efficient lookups. If you can't include the row key in your query, the database must scan all nodes, defeating the purpose of the system.

When should you NOT use a column-family store?

When you need flexible ad-hoc queries with JOINs and complex WHERE clauses, Column-family stores don't support JOINs and require queries to include the row key. If you need flexible ad-hoc querying, a relational database or search engine is a much better fit.

Column-Family Stores

Name: System Design Masterclass
Availability: InStock

in Database Types Storage

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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All 766 interactive lessons

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