Exploring Vector, Time¿Series, Graph, Columnar/OLAP, and Geospatial Databases in the Wild
Buch, Englisch, 187 Seiten, Format (B × H): 178 mm x 254 mm
ISBN: 979-8-8688-2708-2
Verlag: APRESS L.P.
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
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
- Geowissenschaften Geologie GIS, Geoinformatik
- Mathematik | Informatik EDV | Informatik Technische Informatik Netzwerk-Hardware
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung
Weitere Infos & Material
1. Foundations of SQL and NoSQL: The Basics of Relational and Non-Relational Databases.- 2. Columnar/OLAP Databases: Large-Scale Aggregation.- 3. Lakehouse Table Formats: ACID Tables on Object Storage.- 4. Event-Stream and Append-Only Databases: Managing Sequential, Immutable Data.- 5. Time-Series Databases: Handling High-Volume Temporal Data.- 6. Probabilistic/Approximate Databases: Trading Accuracy for Efficiency.- 7. Vector Databases and High-Dimensional Search: Semantic Similarity at Scale.- 8. Graph Databases: Modeling Highly Connected Data.- 9. Geospatial and Spatial Databases: Storing and Querying Location-Based Data.- 10. Choosing the Right Engine and Hybrid Architectures.
