ClickHouse for Real-Time Data Engineering: A Project-Based Guide to High-Performance Analytics with SQL, Kafka, Streaming Pipelines, Observability, and Production Scale - Softcover

Inhaltsangabe

Feeling overwhelmed by real-time analytics, streaming pipelines, or high-performance databases? You are not alone. ClickHouse can look intimidating at first, but you do not need previous ClickHouse experience to begin. This book guides you step by step from the fundamentals to production-ready data engineering, using clear explanations, practical exercises, and a complete project that grows with you.

ClickHouse for Real-Time Data Engineering is a hands-on guide to building fast, reliable analytical systems with SQL, Kafka, materialized views, observability, and distributed architecture. Basic familiarity with SQL, databases, and data-pipeline concepts is helpful, but the ClickHouse-specific ideas are introduced gradually so you can learn with confidence. ClickHouse_for_Real-Time_Data_E…

Key Features

• Beginner-friendly progression from architecture and data modeling to production operations
• Practical, project-based learning built around a real-time product analytics platform
• Clear explanations of MergeTree tables, sorting keys, partitions, ingestion, and query optimization
• Real-world Kafka streaming, materialized views, observability, replication, security, and recovery
• Hands-on exercises that encourage experimentation, troubleshooting, and steady progress
• Production-focused guidance for scaling, backups, capacity planning, reliability, and cost

What You Will Learn

• Design efficient analytical schemas for ClickHouse
• Choose MergeTree engines, ORDER BY keys, partitions, and data types
• Build sustainable high-throughput ingestion pipelines
• Connect Kafka to ClickHouse and handle replay, retries, backpressure, and failures
• Use materialized views, rollups, and aggregate states
• Write and tune analytical SQL with EXPLAIN, query logs, projections, and indexes
• Build observability pipelines with logs, metrics, traces, and OpenTelemetry
• Scale with replication, sharding, distributed queries, and workload isolation
• Apply security, retention, backup, restore, and production-readiness practices

Who This Book Is For

This book is ideal for developers, data engineers, analysts, students, and self-learners who want a practical introduction to ClickHouse and real-time analytics. It is especially useful if you understand basic SQL and database concepts but want a guided path into streaming data, analytical modeling, performance tuning, and production-scale systems.

Table of Contents

Chapter 1: ClickHouse Architecture and Analytical Data Modeling
Chapter 2: MergeTree Tables and Physical Data Design
Chapter 3: High-Throughput Data Ingestion
Chapter 4: Kafka and Real-Time Streaming Pipelines
Chapter 5: Materialized Views, Transformations, and Aggregation
Chapter 6: Analytical SQL and Query Performance Engineering
Chapter 7: Observability Analytics and Monitoring ClickHouse
Chapter 8: Replication, Sharding, and Distributed ClickHouse
Chapter 9: Security, Reliability, and Data Lifecycle Engineering
Chapter 10: Production Architecture, Operations, and Cost Engineering ClickHouse_for_Real-Time_Data_E…

Mistakes are part of learning. Every working table, successful pipeline, faster query, and solved production problem is progress. If you are ready to move from ClickHouse basics to building complete real-time analytical systems, start your data engineering journey today with a practical guide designed to help you learn by doing.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.