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Getting Started with RethinkDB

You're reading from   Getting Started with RethinkDB Absorb the knowledge required to utilize, manage, and deploy

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Product type Paperback
Published in Mar 2016
Publisher Packt
ISBN-13 9781785887604
Length 176 pages
Edition 1st Edition
Languages
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Author (1):
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Gianluca Tiepolo Gianluca Tiepolo
Author Profile Icon Gianluca Tiepolo
Gianluca Tiepolo
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Table of Contents (9) Chapters Close

Preface 1. Introducing RethinkDB FREE CHAPTER 2. The ReQL Query Language 3. Clustering, Sharding, and Replication 4. Performance Tuning and Advanced Queries 5. Programming RethinkDB in Node.js 6. RethinkDB Administration and Deployment 7. Developing Real-Time Web Applications 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...

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