Скачать или смотреть Internals and design of NoSQL databases | How it scales and manages consistency seamlessly

In this deep dive, we explore how some of the world’s largest platforms — like Amazon , YouTube , and Netflix — scale their databases to handle billions of requests per day , while maintaining availability , performance , and data consistency in the face of massive traffic spikes (like Amazon’s Big Billion Day!).

We’ll walk through:

🔁 Distributed Systems Fundamentals : Partitioning, replication, and fault tolerance.
🧱 Consistent Hashing vs DynamoDB’s Approach : How AWS manages partitioning behind the scenes.
💾 Storage Internals : From memtables , commit logs , and SSTables — how databases like Cassandra and RocksDB manage writes efficiently.
🔍 Bloom Filters & Indexing : Why they're crucial for fast reads and avoiding unnecessary disk I/O.
📚 SQL vs NoSQL at Scale : When each shines — with real-world use cases from YouTube (MySQL), Netflix (Cassandra), and Spotify (Cassandra + Redis).
🧩 Multi-Primary Databases & Conflict Resolution : How concurrent writes can lead to inconsistencies — and how CRDTs, vector clocks, and merge logic help resolve them.
🔄 Hinted Handoff, Anti-Entropy, and Gossip Protocols : How systems detect failures and maintain consistency during outages.
📊 Document DB vs Key-Value Stores : Use cases where MongoDB shines over Redis or DynamoDB.
🤯 Real-World Case Study : A user shopping on Amazon during Big Billion Day — how cart data is stored across replicas, what happens when multiple regions write concurrently, and how conflict resolution ensures global consistency.
----------------------

Who Is This For?
✅ Software Engineers
✅ Data Engineers
✅ DevOps / SREs
✅ Tech Leads
✅ Anyone interested in how big systems work at scale

------------------------------

What You'll Learn:
✅ How databases scale horizontally using sharding and replication
✅ The pros and cons of multi-primary architectures
✅ Why Bloom filters are used in SSTable-based systems
✅ How Merkle trees help detect inconsistencies in distributed databases
✅ Real-world trade-offs between SQL and NoSQL
✅ How to avoid split-brain scenarios and ensure eventual consistency