Book Image

Getting Started with RethinkDB

By : Gianluca Tiepolo
Book Image

Getting Started with RethinkDB

By: Gianluca Tiepolo

Overview of this book

RethinkDB is a high-performance document-oriented database with a unique set of features. This increasingly popular NoSQL database is used to develop real-time web applications and, together with Node.js, it can be used to easily deploy them to the cloud with very little difficulty. Getting Started with RethinkDB is designed to get you working with RethinkDB as quickly as possible. Starting with the installation and configuration process, you will learn how to start importing data into the database and run simple queries using the intuitive ReQL query language. After successfully running a few simple queries, you will be introduced to other topics such as clustering and sharding. You will get to know how to set up a cluster of RethinkDB nodes and spread database load across multiple machines. We will then move on to advanced queries and optimization techniques. You will discover how to work with RethinkDB from a Node.js environment and find out all about deployment techniques. Finally, we’ll finish by working on a fully-fledged example that uses the Node.js framework and advanced features such as Changefeeds to develop a real-time web application.
Table of Contents (15 chapters)
Getting Started with RethinkDB
Credits
About the Author
Acknowledgement
About the Reviewer
www.PacktPub.com
Preface
Index

Sharding


Sharding (or partioning) can be defined as the process of splitting a table across multiple machines. This is achieved by dividing a table into multiple parts and putting a subset of data on each machine. Sharding a table allows us to store more data and handle more load without scaling vertically (that is, no need for larger and more powerful machines).

Note

If you haven't worked on scaling a database before, you may be confused about the differences between replication and sharding. Replication creates an exact copy of a table on a different server, whereas sharding distributes the table such that each server has a portion of the data of each table.

Sharding a database solves the challenges of scaling to support very large datasets. In fact, sharding reduces the number of operations that each shard handles, resulting in an increased capacity. Additionally, sharding reduces the amount of data that each server needs to store.

One of the benefits of RethinkDB's sharding implementation...