Eventual Consistency

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 12 is a summary of the book and a visionary view of the future.

• Data Integration.
  • Overview of the ways we have to integrate data.
  • Causality and why we need Total Order and Idempotency.
  • Transactions and Linearizability
  • Limitations of Total Order.
  • Lambda architecture and unifying batch and stream processing as the most perspective approach.
• Unbundling Databases.
  • Overview of composing data storages together.
  • Designing apps around Dataflow.
  • Usage of derived states.
• Aiming for Correctness: what problems to consider and how to deal with them.
  • End-to-end fencing token.
  • How to process multi-partition requests.
  • Timeliness and Integrity issues. Apology workflow in business.
  • Meta approach: Trust, but Verify.
• Doing the Right Thing.
  • Predictive Analytics is discriminating people! We have responsibility and accountability here.
  • Privacy is conflicting with Tracking. Total surveillance should be legislated and self-regulated.

Download full mind map (PDF)

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:

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 7 is all your DEV team should know about Transactions:

• The purpose of transactions
• The concept of transaction: ACID, BASE, single-object and multi-object transactions
• Weak Isolation Levels: Read Committed, Snapshot Isolation and Repeatable Read. Problems and preventing them: Lost Updates, Write Skew and Phantoms
• Serializability and three approaches: Actual Serial Execution, Two-Phase Locking (2PL), Serializable Snapshot Isolation (SSI). Potential problems and performance.

Download full mind map (PDF)

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 5:

• Intro. How to scale apps. Replicating and partitioning.
• Three algos of replicating
• Single-leader Replication
  • Leaders and Followers
  • Sync and async replication
  • Adding new Followers
  • Handling node outages
  • Technical implementations and all potential problems
• Multi-Leader Replication
  • Use-cases when it is good
  • Handling write conflicts
  • Three topologies and potential problems
• Leaderless Replication
  • Writing to the database when a node is down
  • Quorums and problems with them
  • Detecting concurrent writes and how to resolve them

Download full mind map (PDF)