CAP Theorem

Key-Value stores are the most basic but widely used data storages.

Design of key-value store consists of understanding the following topics:

• What do we want from key-value store?
• Single server key-value store
• DISTRIBUTED key-value store:
  • CAP theorem
  • Real-world trade-offs for distributed systems
• System components:
  • Data partition
  • Data replication
  • Consistency
  • Inconsistency resolution: Versioning
  • Handling all types of failures: Failure detection, Handling TEMPORARY failures, Handling PERMANENT failures, Handling data center outage
• System architecture diagram
• Write path
• Read path

These items are disclosed in a very interesting Chapter 6 of the book:

Earlier the book club of our company has studied excellent book:

Martin Kleppmann - Designing Data-Intensive Applications

This is the best book I have read about building complex scalable software systems. 💪

As usually I prepared an overview and mind-map.

Chapter 9 tells about Consistency and Consensus in distributed systems. It covers the following topics:

• What is consistency and eventual consistency
• Linearizability. Why it is needed. Difference from Serializability. How to implement Linearizability. The cost of Linearizability. CAP theorem.
• Ordering Guarantees. What is ordering and causality. It’s relation to Linearizability. Sequence Number Ordering and how to implement it. Total Order Broadcast and how to implement it.
• Distributed Transactions and Consensus. Why we need Consensus and Distributed Transactions. How to implement them, related problems and software that helps.

Summary: