How an RDBMS works #2: Reasons to study its design
Tags: apacheage, rdbms, data
Published: 2023-03-18 23:17:29

This is the second article of [the series](https://dev.to/carlasanches/how-an-rdbms-works-lessons-from-the-internals-of-postgresql-1-45i4) about the operation of a Relational Database Management System (RDBMS) based on PostgreSQL. After reading the book "Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more" by Lightstone, Teorey, and Nadeau (2010), I found it relevant to write about why understanding database design is very important.

In a brief summary of what the authors bring as motivation, the volume of data in the world tends to grow exponentially. As the volume of data increases, so does the demand for more robust data structures to securely store data and return queries faster and faster.

According to Andre (2023), the amount of data created daily on the internet is 1.134 trillion MB. Lately, this increase has been mainly due to the popularization of social media and streaming services. If in 2010 we were talking about petabytes, Figure 1 presents the estimate of data consumption in zettabytes since 2021, which is expected to double by 2024.

<figure>
  <img src="https://dev-to-uploads.s3.amazonaws.com/uploads/articles/aejl1ux5wnqcgdypbj3j.png"
  alt="Estimated data consumption from 2021 to 2024.">
  <figcaption>Figure 1 - Estimated data consumption from 2021 to 2024. Adapted from Andre (2023).</figcaption>
</figure>

In addition, new technologies are continuously emerging to help make sense of this data. For example, [Bitnine Global Inc.](https://bitnine.net/) has [Apache AGE](https://age.apache.org/) to provide graph data analysis for relational databases. [G-FDS](https://bitnine.net/g-fds/) is a graph-based solution for fraud detection, and [G-PAS](https://bitnine.net/g-fds/) focuses on predictive analysis for Big Data. There are other products and more new developments on the horizon! Therefore, understanding the foundation and needs of database structures is essential to deliver quality solutions. In the next post, I will discuss the life cycle of an RDBMS and explain the architecture of PostgreSQL in practice.

## Errata

My intention is to provide access to technology information through reliable sources. If you have found any incorrect information, please let your contribution in the comments below 😊.

## Related Articles

- [How an RDBMS works #1: Lessons from “The Internals of PostgreSQL”](https://dev.to/carlasanches/how-an-rdbms-works-lessons-from-the-internals-of-postgresql-1-45i4)

- [Apache AGE : What it is and Tutorials](https://dev.to/matheusfarias03/apache-age-what-it-is-and-tutorials-2egh)

- [What is Apache AGE®](https://dev.to/farakhshahid/what-is-apache-ager-2iee)

- [Exploring the Postgres Internals: A Guide for Database Admins and System Developers (Part 1)](https://dev.to/adeelahmed2k01/exploring-the-postgres-internals-a-guide-for-database-admins-and-system-developers-part-1-509i)

## References

Lightstone, Sam S., Toby J. Teorey, and Tom Nadeau. *Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more*. Morgan Kaufmann, 2010.

Andre, Louie. 53 Important Statistics About How Much Data Is Created Every Day. Finances Online. 2023. Available at [https://financesonline.com/how-much-data-is-created-every-day/](https://financesonline.com/how-much-data-is-created-every-day/). Acessed on 03/15/2023.

## Contribute to Apache AGE

Apache AGE website: [https://age.apache.org/](https://age.apache.org/)

Apache AGE Github: [https://github.com/apache/age](https://github.com/apache/age)