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Erschienen: 25.09.2026

The Database Safari

Exploring Vector, Time-Series, Graph, Columnar/OLAP, and Geospatial Databases in the Wild

Apress

ISBN 979-8-8688-2709-9

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Bibliografische Daten

eBook. PDF. Weiches DRM (Wasserzeichen)

2026

6 s/w-Abbildungen.

In englischer Sprache

Umfang: 346 S.

Verlag: Apress

ISBN: 979-8-8688-2709-9

Produktbeschreibung

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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