Get introduced to PostgreSQL and learn about the tools and modules used in PostgreSQL.

Why PostgreSQL?

While we learn SQL and how to make the best of this programming language in modern application development, we’ll also see the PostgreSQL implementation of the SQL standard. That choice is down to several factors, as given below:

  • PostgreSQL is open source, available under a BSD-like license, named the PostgreSQL license.

  • The PostgreSQL project is done completely in the open, using public mailing lists for all discussions, contributions, and decisions. The project goes as far as self-hosting all requirements in order to avoid being influenced by a particular company.

  • While PostgreSQL is developed and maintained in the open by volunteers, most PostgreSQL developers today are contributing in a professional capacity, both in the interests of their employers and by solving customer problems.

  • PostgreSQL releases a new major version about once a year, following a “when it’s ready” release cycle.

  • Ever since its Berkeley days under the supervision of Michael StonebrakerMichael Ralph Stonebraker, is a computer scientist specializing in database systems., the PostgreSQL design allows for enhancing SQL in very advanced ways.

  • The PostgreSQL documentation is one of the best reference manuals we can find, open source or not. That’s because a patch in the code is only accepted when it also includes editing the parts of the documentation that need it.

  • While new NoSQL systems are offering different trade-offs in terms of operations, guarantees, query languages, and APIs, we would argue that PostgreSQL is YeSQLYeSQL stands for You extend SQL. It’s a library by Kris Jenkins..

In particular, the extensibility of PostgreSQL allows this 20-year-old system to keep renewing itself. As a data point, this extensibility design makes PostgreSQL one of the best JSON processing platforms.

The extensibility design of PostgreSQL also makes it possible to improve SQL with advanced support for new data types, even from “userland code,” and to integrate processing functions and operators and their indexing support.

We’ll see lots of examples of that kind of integration. One of them is a query used in the Schemaless Design in PostgreSQL, an upcoming lesson, where we deal with a set of cards (Magic: The Gathering™) imported from a JSON dataset:

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