Скачать или смотреть Designing Data-Intensive Applications (EP 1) Reliability, Scalability, and Maintainability Explained

This video breaks down Part I: Foundations of Data Systems from Martin Kleppmann’s Designing Data-Intensive Applications (DDIA) the most influential book on modern system design and data architecture.

We explore the essential principles behind building reliable, scalable, and maintainable applications, with simple examples and intuitive visuals that make complex ideas easy to understand.

🔥 What You’ll Learn
1. Reliability, Scalability & Maintainability

Understand the three pillars of system design:

Reliability: how systems survive hardware failures, software bugs, and human mistakes.

Scalability: what happens when data or traffic grows, and why we measure performance using latency percentiles.

Maintainability: designing systems that evolve safely over years not months.

2. Data Models & Query Languages

A clear comparison of:

Relational databases vs Document (NoSQL) stores

When to use graph-like models

How declarative query languages like SQL, Cypher, SPARQL empower flexible data access

3. Storage Engines: B-Trees & LSM-Trees

Discover how databases store and retrieve data efficiently:

B-Trees for update-in-place storage

LSM-Trees for write-optimized, log-structured storage
We also simplify the difference between OLTP and OLAP, including why analytics systems rely on column-oriented storage.

4. Encoding & Schema Evolution

Learn how data is encoded for transmission and storage:

Textual formats (JSON, XML)

Binary formats (Thrift, Protocol Buffers, Avro)
We explain schema evolution, compatibility rules, and how data flows between services via databases, RPC/REST, and message queues.

🎯 Who This Video Is For

This is a must-watch for:

Software engineers preparing for system design interviews

Backend developers learning data architecture fundamentals

Data engineers who want deeper intuition into storage & retrieval

Anyone studying or summarizing DDIA

If you're learning system design, this episode will give you the mental models you need to understand why modern data systems are built the way they are.

👍 Call to Action

If you want Parts 2 & 3, comment “DDIA!”
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