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基本説明
The book guides readers through building a small 4×4×4 LED cube and creating a block‑based interface to control it. Using this focused project, it demonstrates key computing concepts, including web design, web servers, databases, communications, and hardware integration, while producing a polished and engaging physical artefact.
Full Description
Pack your field kit—this is a guided safari through today's database ecosystem. In the wild, one size rarely fits all: Modern systems often need specialized databases to deliver real‑world performance and scale. This book is a practical field guide to those less commonly used databases—vector, time‑series, graph, columnar/OLAP, geospatial, event‑stream, and more. It shows you how each engine works, where it excels, and how to choose the right engine for each workload. The book provides clear trade‑off tables, indexing strategies, query patterns, and use‑case recipes you can apply immediately.
Starting with foundations in SQL and NoSQL, this book explores each "species" chapter by chapter, emphasizing hands‑on scenarios and pitfalls to avoid. It then brings everything together in polyglot/hybrid architectures, helping you combine engines confidently, whether you're designing a similarity search with vector databases (ANN), building observability pipelines on time‑series data and event logs, modeling relationships in graph databases, or delivering analytics with columnar/OLAP and geospatial queries. The result is a concise, engineer‑first map of the database landscape that turns theory into pragmatic decision‑making.
What You Will Learn
Identify the right engine for the job across vector, time‑series, graph, columnar/OLAP, geospatial, and event‑stream databases
Evaluate trade‑offs in performance, scalability, consistency, storage layout, indexing, and operational complexity
Design polyglot architectures that combine multiple engines (e.g., vector + OLAP + event‑stream) for end‑to‑end solutions
Apply use‑case patterns for similarity search (ANN), observability metrics, fraud/network analysis, geospatial routing, and analytical reporting
Understand core internals that matter (index types, retention policies, log‑structured storage, spatial indexes, columnar execution) without vendor lock‑in
Avoid common pitfalls in schema design, query planning, and cross‑engine data movement
Build a decision checklist and trade‑off tables to justify engine selection to stakeholders
Who This Book Is For
Software engineers; back-end developers; data engineers; system architects; site reliability engineers (SREs); technical leads with basic SQL/NoSQL experience who need practical guidance to select, compare, and combine specialized databases for real‑world applications
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