Dan Sullivan

NoSQL for Mere Mortals (eBook, ePUB)

• Format: ePub

Produktbeschreibung

The Easy, Common-Sense Guide to Solving Real Problems with NoSQL

The Mere Mortals® tutorials have earned worldwide praise as the clearest, simplest way to master essential database technologies. Now, there's one for today's exciting new NoSQL databases. NoSQL for Mere Mortals guides you through solving real problems with NoSQL and achieving unprecedented scalability, cost efficiency, flexibility, and availability.

Drawing on 20+ years of cutting-edge database experience, Dan Sullivan explains the advantages, use cases, and terminology associated with all four main categories of NoSQL databases: key-value, document, column family, and graph databases. For each, he introduces pragmatic best practices for building high-value applications. Through step-by-step examples, you'll discover how to choose the right database for each task, and use it the right way.

Coverage includes

--Getting started: What NoSQL databases are, how they differ from relational databases, when to use them, and when not to Data management principles and design criteria: Essential knowledge for creating any database solution, NoSQL or relational

--Key-value databases: Gaining more utility from data structures

--Document databases: Schemaless databases, normalization and denormalization, mutable documents, indexing, and design patterns

--Column family databases: Google's BigTable design, table design, indexing, partitioning, and Big Data

Graph databases: Graph/network modeling, design tips, query methods, and traps to avoid

Whether you're a database developer, data modeler, database user, or student, learning NoSQL can open up immense new opportunities. As thousands of database professionals already know, For Mere Mortals is the fastest, easiest route to mastery.

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Produktdetails

• Verlag: Pearson ITP
• Seitenzahl: 552
• Erscheinungstermin: 6. April 2015
• Englisch
• ISBN-13: 9780134029887
• Artikelnr.: 42640480

Autorenporträt

Dan Sullivan is a data architect and data scientist with more than 20 years of experience in business intelligence, machine learning, data mining, text mining, Big Data, data modeling, and application design. Dan's project work has ranged from analyzing complex genomics and proteomics data to designing and implementing numerous database applications. His most recent work has focused on NoSQL database modeling, data analysis, cloud computing, text mining, and data integration in life sciences. Dan has extensive experience in relational database design and works regularly with NoSQL databases. Dan has presented and written extensively on NoSQL, cloud computing, analytics, data warehousing, and business intelligence. He has worked in many industries, including life sciences, financial services, oil and gas, manufacturing, health care, insurance, retail, power systems, telecommunications, pharmaceuticals, and publishing.