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    Ontotext GraphDB in Practice: The Complete Guide for Developers and Engineers

    Posted By: naag
    Ontotext GraphDB in Practice: The Complete Guide for Developers and Engineers

    Ontotext GraphDB in Practice: The Complete Guide for Developers and Engineers
    English | July 24, 2025 | ASIN: B0FJYG1P3J | 261 pages | EPUB (True) | 1.73 MB

    "Ontotext GraphDB in Practice"

    "Ontotext GraphDB in Practice" delivers a comprehensive, hands-on guide to leveraging the full power of semantic graph databases for modern enterprise use. Beginning with the fundamentals of graph data modeling and the W3C Semantic Web stack, the book offers a clear exposition of RDF, knowledge graphs, and the capabilities that set Ontotext GraphDB apart in a fast-evolving data landscape. It explores real-world use cases across publishing, pharma, and cultural heritage, while imparting a critical understanding of the challenges and opportunities inherent to large-scale graph-based systems.

    This book equips data architects, engineers, and decision-makers with end-to-end expertise in deploying, configuring, and optimizing GraphDB in both standalone and clustered environments. Readers are guided through semantic data modeling, ontology management, robust data integration, and advanced SPARQL querying, with detailed attention to scalability, high availability, and security. Practical recipes, architectural best practices, and proven deployment patterns help organizations harness flexible interoperability with cloud, data lakes, streaming platforms, BI tools, and AI-driven analytics.

    Expertly structured to address both foundational knowledge and advanced operational disciplines, "Ontotext GraphDB in Practice" emphasizes enterprise integration, compliance, governance, and the relentless pursuit of data quality. Drawing on case studies and field-tested techniques, it illuminates the path from effective graph modeling to deploying mission-critical knowledge graphs that transform how businesses unify, analyze, and act on information. This book is an indispensable reference for building resilient, future-proof semantic data solutions at scale.