Discover references
NoSQL
Explore the World of NoSQL Databases
NoSQL databases have revolutionized the way we handle data, providing immense flexibility and scalability compared to traditional relational databases. In this category, discover an extensive selection of books that delve into the expansive universe of NoSQL databases, offering insights for both beginners and experts.
Understanding NoSQL Concepts
NoSQL, or “Not Only SQL”, databases are designed to tackle large-scale storage and processing challenges that conventional relational databases struggle with. Unlike SQL databases, which use structured query language and table-based data structures, NoSQL databases utilize a variety of data models, including document, key-value, column-family, and graph formats. This flexibility allows for more agile development and scalability when dealing with complex, high-volume data.
Books in this section provide a fundamental understanding of the four primary types of NoSQL databases: Document-oriented databases such as MongoDB; Key-Value Stores like Redis; Columnar Stores, with Apache Cassandra as an example; and Graph Databases, exemplified by Neo4j. Readers will learn when and why to choose NoSQL solutions over traditional databases, gaining insight into the use-cases and trade-offs associated with each NoSQL category.
Implementation and Best Practices
Once you grasp the essential concepts of NoSQL databases, the next step is learning how to implement these systems efficiently and effectively. Our collection includes books that guide you through the process of deploying and managing NoSQL databases, with a focus on practical skills and best practices.
You will find information on setting up and configuring popular NoSQL databases, data modeling, indexing, and query techniques specific to each type. Moreover, these resources discuss distributed architectures and fault tolerance mechanisms, helping you understand how to maintain data consistency and reliability at scale.
The section also covers topics such as backup strategies, performance optimization, and monitoring tools to ensure that your systems run smoothly and efficiently, meeting the demands of contemporary applications.
Advanced Topics in NoSQL
For those who are ready to advance their understanding, this category offers books on cutting-edge NoSQL topics such as data streaming, real-time analytics, and cloud integration. Readers can explore how NoSQL databases can be leveraged for big data processing and how they integrate with other technologies like Hadoop and Apache Kafka.
Additionally, delve into the realms of data security in NoSQL environments, learn about the challenges and solutions in sharding and scaling, and explore innovative uses of machine learning with NoSQL data. This section is valuable for tech professionals seeking to keep abreast of the latest developments and innovations in this fast-evolving field.
Case Studies and Real-Life Applications
To truly understand the power of NoSQL databases, it is essential to see how they are applied in real-world scenarios. This division of our NoSQL book selection includes comprehensive case studies and success stories from various industries.
Gain insights from companies that have successfully implemented NoSQL solutions to solve critical business challenges. Learn how e-commerce giants, social media platforms, and mobile applications leverage NoSQL databases to handle millions of transactions and users daily.
These books provide a practical perspective, showing you how to harness the flexibility and scalability of NoSQL databases for your own projects and organizational needs.
Conclusion: Empower Your Data Strategy with NoSQL
Whether you are just beginning your journey into NoSQL databases or are looking to expand your expertise, our curated collection of books in this category serves as a comprehensive resource. From foundational texts to advanced guides, every book is selected to empower you to utilize NoSQL databases to their fullest potential.
Dive into the world of NoSQL databases today and unlock new levels of data efficiency and scalability for your projects.
Books
128 resultsHands-On Big Data Modeling Effective database design techniques for data architects and business intelligence professionals
James Lee,Tao Wei,Suresh Kumar Mukhiya
The Definitive Guide to MongoDB, 3rd Edition: A complete guide to dealing with Big Data using MongoDB
David Hows, Eelco Plugge, Peter Membrey, Tim Hawkins
Learn Amazon SageMaker: A guide to building, training, and deploying machine learning models for developers and data scientists
Julien Simon
MongoDB in Action: Covers MongoDB version 3.0
Kyle Banker,Peter Bakkum,Shaun Verch,Doug Garrett,Tim Hawkins
MongoDB Fundamentals: A hands-on guide to using MongoDB and Atlas in the real world
Amit Phaltankar,Juned Ahsan,Michael Harrison,Liviu Nedov
Machine Learning - Hands-On for Developers and Technical Professionals (Java).
Jason Bell
Global Seismicity Dynamics and Data-Driven Science: Seismicity Modelling by Big Data Analytics
Mitsuhiro Toriumi
Applied architecture patterns on the Microsoft platform : an in-depth, scenario-driven approach to architecting systems using Microsoft technologies
Richard Seroter;Ofer Ashkenazi; et al
Cassandra: the definitive guide: [distributed data at web scale]
Hewitt, Eben
Beyond Databases, Architectures, and Structures: 10th International Conference, BDAS 2014, Ustron, Poland, May 27-30, 2014. Proceedings
Stanislaw Kozielski,Dariusz Mrozek,Pawel Kasprowski,Bożena Małysiak-Mrozek,Daniel Kostrzewa (eds.)
Mastering MongoDB 4.x : expert techniques to run high-volume and fault-tolerant database solutions using MongoDB 4.x
Alex Giamas
The Definitive Guide to MongoDB: A Complete Guide to Dealing with Big Data Using MongoDB
David Hows,Peter Membrey,Eelco Plugge,Tim Hawkins (auth.)
The Definitive Guide to MongoDB, 3rd Edition: A complete guide to dealing with Big Data using MongoDB
David Hows,Eelco Plugge,Peter Membrey,Tim Hawkins
Couchbase Essentials: Harness the power of Couchbase to build flexible and scalable applications
John Zablocki
Pig design patterns: simplify Hadoop programming to create complex end-to-end enterprise big data solutions with Pig
Pradeep Pasupuleti
Stream Analytics with Microsoft Azure: Real-time data processing for quick insights using Azure Stream Analytics
Anindita Basak,Krishna Venkataraman,Ryan Murphy,Manpreet Singh
Data Science and Big Data Analytics in Smart Environments
Marta Chinnici (editor),Florin Pop (editor),Catalin Negru (editor)
Big Data Science and Analytics for Smart Sustainable Urbanism: Unprecedented Paradigmatic Shifts and Practical Advancements
Simon Elias Bibri
Programming Hive. Data Warehouse and Query Language for Hadoop
Edward Capriolo,Dean Wampler,Jason Rutherglen
Practical MongoDB: Architecting, Developing, and Administering MongoDB
Shakuntala Gupta Edward,Navin Sabharwal
Pro Hadoop Data Analytics : Designing and Building Big Data Systems using the Hadoop Ecosystem
Kerry Koitzsch (auth.)
Practical Hadoop Migration: How to Integrate Your RDBMS with the Hadoop Ecosystem and Re-Architect Relational Applications to NoSQL
Bhushan Lakhe (auth.)
Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation: 13th International Conference, BDAS 2017, Ustroń, Poland, May 30 - June 2, 2017, Proceedings
Stanisław Kozielski,Dariusz Mrozek,Paweł Kasprowski,Bożena Małysiak-Mrozek,Daniel Kostrzewa (eds.)
Advanced Analytics with Spark: Patterns for Learning from Data at Scale
Sandy Ryza,Uri Laserson,Sean Owen,Josh Wills
Mastering MongoDB 3.x an expert's guide to building fault-tolerant MongoDB applications
Giamas,Alex