Graph Databases in Action - (In Action) by Dave Bechberger & Josh Perryman (Paperback)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><b><i>Graph Databases in Action</i> introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization.</b> <p/><b>Summary</b><br> Relationships in data often look far more like a web than an orderly set of rows and columns. Graph databases shine when it comes to revealing valuable insights within complex, interconnected data such as demographics, financial records, or computer networks. In <i>Graph Databases in Action</i>, experts Dave Bechberger and Josh Perryman illuminate the design and implementation of graph databases in real-world applications. You'll learn how to choose the right database solutions for your tasks, and how to use your new knowledge to build agile, flexible, and high-performing graph-powered applications! <p/> Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. <p/> <b>About the technology</b><br> Isolated data is a thing of the past! Now, data is connected, and graph databases--like Amazon Neptune, Microsoft Cosmos DB, and Neo4j--are the essential tools of this new reality. Graph databases represent relationships naturally, speeding the discovery of insights and driving business value. <p/> <b>About the book</b><br> <i>Graph Databases in Action</i> introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization. <p/> <b>What's inside</b><br> Graph databases vs. relational databases<br> Systematic graph data modeling<br> Querying and navigating a graph<br> Graph patterns<br> Pitfalls and antipatterns <p/><b>About the reader</b><br> For software developers. No experience with graph databases required. <p/> <b>About the author</b><br> <b>Dave Bechberger</b> and <b>Josh Perryman</b> have decades of experience building complex data-driven systems and have worked with graph databases since 2014. <p/> <b>Table of Contents</b> <p/>PART 1 - GETTING STARTED WITH GRAPH DATABASES <p/>1 Introduction to graphs <p/>2 Graph data modeling <p/>3 Running basic and recursive traversals <p/>4 Pathfinding traversals and mutating graphs <p/>5 Formatting results <p/>6 Developing an application <p/>PART 2 - BUILDING ON GRAPH DATABASES <p/>7 Advanced data modeling techniques <p/>8 Building traversals using known walks <p/>9 Working with subgraphs <p/>PART 3 - MOVING BEYOND THE BASICS <p/>10 Performance, pitfalls, and anti-patterns <p/>11 What's next: Graph analytics, machine learning, and resources<p/><br></br><p><b> About the Author </b></p></br></br>Dave Bechberger has extensive experience using graph databases as a product architect and a consultant. He's spent his career leveraging cutting- edge technologies to build software in complex data domains such as bioinformatics, oil and gas, and su <p/>Josh Perryman is technologist with over two decades of diverse experience building and maintaining complex systems, including high performance computing (HPC) environments. Since 2014 he has focused on graph databases, especially in distributed or big data environments, and he regularly blogs and speaks at conferences about graph databases.
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