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Links to Free Computer, Mathematics, Technical Books all over the World
NoSQL and Non-relational Databases
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  • Guide to NoSQL with Azure Cosmos DB (Gaston C. Hillar, et al)

    This book is for C# developers. This book starts off by showing you the main features of Cosmos DB, their supported NoSQL data models and the foundations of its scalable and distributed architecture.

  • Graph Databases for Beginners (Bryce Merkl Sasaki, et al)

    This book takes those new to the world of connected data through the basics of graph technology - whether you're a business executive or a seasoned developer, something has led you on the quest to learn more about graph technology - what it does for you.

  • Graph Databases and Neo4J (Anna Turu Pi, et al)

    The aim of this book is to compare graph databases to the main DBMSs to pinpoint the use cases it is more suitable for. In order to prove their effectiveness, a database using the same data set has been implemented both in Neo4j and SQL Server.

  • O'Reilly® Graph Databases: New Opportunities for Connected Data

    This book provides a practical foundation for those who want to apply Graph Database to real-world business solutions. You'll learn why graph database are useful, where they're applicable, and how to design and implement solutions that use them.

  • O'Reilly® CouchDB: The Definitive Guide (J. Chris Anderson, et al)

    This book teaches the fundamentals of one of the most powerful database engines ever created for the price of a good lunch.

  • Apache Cassandra Succinctly (Marko Svaljek)

    Step outside the relational world and learn how to store data with Apache Cassandra, the massively popular NoSQL distributed database system. You will be able to store and model data using the Cassandra Query Language, and use Cassandra within your own apps.

  • Firebase Essentials - Android Edition (Neil Smyth)

    This book provides everything you need to successfully integrate Firebase cloud features into your Android apps. The book is organized into chapter groups that focus on specific Firebase features, with each topic area consisting of a detailed overview.

  • Instant MongoDB (Amol Nayak)

    This eBook is designed to get you working with MongoDB as quickly as possible. Starting with installation and setup, learn about CRUD operations in MongoDB, its Map Reduce support, schema design, performance tuning operations, and more.

  • Spring Data Programming Cookbook (JCGs)

    It provides a compilation of Spring Data examples that will help you kick-start your own projects. It covers a wide range of topics, from setting up the environment and creating a basic project, to handling the various modules (e.g. JPA, MongoDB, Redis etc.).

  • O'Reilly® Programming Pig (Alan F Gates)

    This book is an ideal learning tool and reference for Apache Pig, the programming language that helps you describe and run large data projects on Hadoop.

  • MongoDB 3 Succinctly (Zoran Maksimovic)

    This book touches on the most important aspects of the MongoDB database that application developers should be aware of—from installation and the usage of the Mongo Shell, to examples of the MongoDB C# driver APIs for Microsoft .NET Framework.

  • Mastering Apache Spark 2.0 (Jacek Laskowski)

    This book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala.

  • HBase Succinctly (Elton Stoneman)

    This book teaches you to use Apache HBase to improve your control of big data. It will detail what makes HBase different from other databases and teach you about its signature features. With this knowledge, you will be able to jump into big data management.

  • MongoDB Succinctly: Quickly Build an Easy-to-manage Database

    Starting with creating a MongoDB database, you'll learn how to make collections and interact with their data, how to build a console application to interact with binary and image collection data, and much more.

  • The Little MongoDB Book (Karl Seguin)

    This little book was written precisely for anyone who is approaching the NoSQL world, but certainly satisfy even the expert who wants to learn more about MongoDB. It was updated to the MongoDB 2.6.

  • The Best of NoSQL (InfoQ eMag)

    This book brings together a selection of popular NoSQL articles recently published on This professionally designed eMag will help you get up to speed on some of the key underlying concepts and trends driving NoSQL adoption.

  • Hadoop Succinctly (Elton Stoneman)

    This booky explains how Hadoop works, what goes on in the cluster, demonstrates how to move data in and out of Hadoop, and how to query it efficiently. It also walks through a Java MapReduce example, illustrates it in Python and .NET, too.

  • Hadoop Illuminated

    Ready to unlock the power of your data? With this mini guide, you will learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop.

  • Good Relationships - The Spring Data Neo4j Guide Book

    This book provides all the practical details you need for developing enterprise applications with Spring Data Neo4j.

  • O'Reilly® Spring Data: Modern Data Access for Enterprise Java

    This book shows you how Spring's data access framework can help you connect to either non-relational or relational databases, or a combination of the two.

  • O'Reilly® HBase: The Definitive Guide (Lars George)

    This book will show you how Apache HBase can fulfill your needs. It provides the details you require, whether you simply want to evaluate this high-performance, non-relational database, or put it into practice right away.

  • Cassandra High Performance Cookbook (Edward Capriolo)

    You can mine deep into the full capabilities of Apache Cassandra using the 150+ recipes in this indispensable Cookbook. From configuring and tuning to using third party applications, this is the ultimate guide.

  • O'Reilly® Agile Data: Building Data Analytics Applications

    How to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) JavaScript library.

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