Book Image

Learning PostgreSQL 11 - Third Edition

By : Salahaldin Juba, Andrey Volkov
Book Image

Learning PostgreSQL 11 - Third Edition

By: Salahaldin Juba, Andrey Volkov

Overview of this book

PostgreSQL is one of the most popular open source database management systems in the world, and it supports advanced features included in SQL standards. This book will familiarize you with the latest features in PostgreSQL 11, and get you up and running with building efficient PostgreSQL database solutions from scratch. Learning PostgreSQL, 11 begins by covering the concepts of relational databases and their core principles. You’ll explore the Data Definition Language (DDL) and commonly used DDL commands supported by ANSI SQL. You’ll also learn how to create tables, define integrity constraints, build indexes, and set up views and other schema objects. As you advance, you’ll come to understand Data Manipulation Language (DML) and server-side programming capabilities using PL/pgSQL, giving you a robust background to develop, tune, test, and troubleshoot your database application. The book will guide you in exploring NoSQL capabilities and connecting to your database to manipulate data objects. You’ll get to grips with using data warehousing in analytical solutions and reports, and scaling the database for high availability and performance. By the end of this book, you’ll have gained a thorough understanding of PostgreSQL 11 and developed the necessary skills to build efficient database solutions.
Table of Contents (18 chapters)

Scalability

In this chapter, we will discuss the problem of scalability. This term means the ability of a software system to grow as the business using it grows. PostgreSQL provides some features that help you to build a scalable solution but, strictly speaking, PostgreSQL itself is not scalable. It can effectively utilize the following resources of a single machine:

  • It uses multiple CPU cores to execute a single query faster with the parallel query feature
  • When configured properly, it can use all available memory for caching
  • The size of the database is not limited; PostgreSQL can utilize multiple hard disks when multiple tablespaces are created; with partitioning, the hard disks could be accesses simultaneously, which makes data processing faster

However, when it comes to spreading a database solution to multiple machines, it can be quite problematic because a standard PostgreSQL...