The Essential Criteria of Graph Databases

Bol

Although AI has incredible potential, it has three weak links: 1. Blackbox, lack of explainability2. Silos, slews of siloed systems across the AI ecosystem3. Low-performance, most of ML/DL based AI systems are SLOW.Fixing these problems will pave the road to strong and effective AI. Graph databases, particularly high-performance graph database or graph computing, should allow this to happen. The Essential Criteria of Graph Databases simply broadens the horizon of graph applications. The book collects several truly innovative graph applications in asset-liability and liquidity risk management, which hopefully will Spark readers' interest in further broaden the reach and applicable domains of graph systems. The essential criteria of graph database(s) are quite different from traditional relational database or other types of NoSQL DBMS or any of those big-data frameworks (i.e., Hadoop, Spark, etc). This book clearly points out the key criteria that readers should pay attention to Avoid common mistakes in and learn how to get hands on with system architecture design, benchmarking or selection of an appropriate graph platform/vendor-system. There are many areas of knowledge surrounding graph technology have long been ignored, hidden (or even forbidden to know), and this book shares them all to the mass public Cultivate graphy thinking is all important in our daily life and how we cruise through this life and world, this book starts with that and hopefully the readers will find interesting and engaging. In another word, cultivate a way of thinking with growth-mindset and without limiting-belief

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Pagina's: 396, Paperback, Elsevier - Health Sciences Division