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Cover for SurrealDB in Depth: The Complete Guide for Developers and Engineers

SurrealDB in Depth: The Complete Guide for Developers and Engineers

Language
English
Format
Category

Non-fiction

"SurrealDB in Depth"

"SurrealDB in Depth" offers a comprehensive and meticulously structured exploration of SurrealDB, the innovative multi-model database designed for modern, distributed applications. This authoritative guide takes readers on a journey through the core architecture of SurrealDB, illuminating its hybrid document-graph storage model, transactional integrity, and advanced concurrency management. Through clear explanations and practical insights, the book examines critical system components—from data storage mechanisms and pluggable storage engines to the intricacies of cluster design, distribution, and performance optimization in real-world environments.

The book goes beyond fundamentals to deliver in-depth treatments of schema modeling, multi-tenancy, and data integrity, ensuring developers can craft robust, scalable applications tailored to diverse business requirements. Readers will find an exhaustive analysis of SurrealQL—the database’s powerful native query language—covering advanced operators, graph traversal, computed logic, and performance best practices. Dedicated chapters demystify API integrations, client SDKs for major programming languages, and essential security models, providing actionable guidance for implementing secure and high-performing data pipelines.

With its holistic perspective, "SurrealDB in Depth" addresses critical operational topics, including monitoring, disaster recovery, zero-downtime upgrades, and incident response. Advanced sections offer case studies on edge computing, IoT, serverless integration, and large-scale multi-region deployments, supplemented by hands-on benchmarking methods and ecosystem insights. Whether you are an architect, developer, or DevOps engineer, this book serves as an essential resource for mastering SurrealDB and unlocking its full potential within cutting-edge data-driven solutions.

© 2025 HiTeX Press (Ebook): 6610000965069

Release date

Ebook: July 12, 2025

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