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The Database Safari: Exploring Vector, Time-Series, Graph, Columnar/OLAP and Geospatial Databases in the Wild
Koos, Gabor
The Database Safari: Exploring Vector, Time-Series, Graph, Columnar/OLAP and Geospatial Databases in the Wild
Koos, Gabor (Author) · Apress · Paperback
The Database Safari: Exploring Vector, Time-Series, Graph, Columnar/OLAP and Geospatial Databases in the Wild
Koos, Gabor
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 databasesEvaluate trade offs in performance, scalability, consistency, storage layout, indexing, and operational complexityDesign polyglot architectures that combine multiple engines (e.g., vector + OLAP + event stream) for end to end solutionsApply use case patterns for similarity search (ANN), observability metrics, fraud/network analysis, geospatial routing, and analytical reportingUnderstand core internals that matter (index types, retention policies, log structured storage, spatial indexes, columnar execution) without vendor lock inAvoid common pitfalls in schema design, query planning, and cross engine data movementBuild a decision checklist and trade off tables to justify engine selection to stakeholdersWho 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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