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Learning PostgreSQL 10

Learning PostgreSQL 10

By : Juba, Volkov
2.3 (6)
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Learning PostgreSQL 10

Learning PostgreSQL 10

2.3 (6)
By: Juba, Volkov

Overview of this book

PostgreSQL is one of the most popular open source databases in the world, supporting the most advanced features included in SQL standards. This book will familiarize you with the latest features released in PostgreSQL 10. We’ll start with a thorough introduction to PostgreSQL and the new features introduced in PostgreSQL 10. We’ll cover the Data Definition Language (DDL) with an emphasis on PostgreSQL, and the common DDL commands supported by ANSI SQL. You’ll learn to create tables, define integrity constraints, build indexes, and set up views and other schema objects. Moving on, we’ll cover the concepts of Data Manipulation Language (DML) and PostgreSQL server-side programming capabilities using PL/pgSQL. We’ll also explore the NoSQL capabilities of PostgreSQL and connect to your PostgreSQL database to manipulate data objects. By the end of this book, you’ll have a thorough understanding of the basics of PostgreSQL 10 and will have the necessary skills to build efficient database solutions.
Table of Contents (17 chapters)
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Summary


OLAP and data warehousing are both used in the context of specific database design patterns, where a database is used for analysis and reporting. OLAP stands for online analytical processing. In contrast to OLTP, OLAP implies bigger amounts of data, a smaller number of concurrent sessions and transactions, but the size of the transactions is bigger. The database structure is often denormalized to improve query performance. A database that is a part of an OLAP solution is often called a data warehouse.

In this chapter, we covered how to structure data in a data warehouse, how to load data there, and how to optimize the database performance by applying partitioning, using parallel query execution, and index-only scans.

In the next chapter, we will discuss the extended data types supported by PostgreSQL such as arrays, JSON, and others. These data types make it possible to implement complicated business logic using native database support.

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