Insights about State of Database 2023

Jorge Mendoza Rivilla
2 min readAug 27, 2023

The survey “State of Databases 2023” created by Basedash was delivered and had insights for the analysis that I talk about in this note.

SQL is the fourth most popular technology for developers (Stack Overflow) and this was the main motivation to obtain insights that allow us to understand the world of databases focused on analytics.

The survey was answered by at least 30 countries and professionals with 3–5 average years of experience. Your scope was Databases: SQL and NoSQL. ORM, hosting, BI tools, Data warehouses, and admin tools.

PostgreSQL takes the lead over MySQL

In the Database category, most professionals use PostgreSQL but also use MySQL, Redis, and MongoDB for NoSQL. In particular, I haven’t heard about Redis which is Open Source and useful to data stored in-memory.

PostgreSQL is an object-relational database management system and this year it beat MySQL as the first option, this insight is correlated with the Stack Overflow survey.

Cloud is trending to Datawarehouse and BigQuery keeps leading

Google BigQuery led on all questions. BigQuery works in the Google Cloud Platform and uses built-in ML/AI and BI for insights at scale. However, Snowflake and Amazon Redshift (both cloud too) also led.

PowerBI and Tableau led the BI Tools, but they are not the most used

Most people know about PowerBI and Tableau, but Metabase and MixPanel are the most used.

The insight is particular, maybe the professionals use PowerBI for the price and the easy usability, but the company has other BI tools because of data architecture, and dependencies or they can pay for the expensive solutions.

I checked some features of Metabase and MixPanel and think that the professional answering the survey working at a company with a digital business or young. Because, when Gartner releases you Magic Cuadrant the BI tools that lead are PowerBI, Tableau, and Qlik.

Fine, in Figure 1 I designed a data stack with the tools that won in the survey (and my favs tools) that help you to understand at which stage you would use these tools.

Figure 1. Data Pipeline idea.

Although the survey had questionable answers I think that is interesting to check some tools that are not on our radar, but we can find it in any company.

If maybe something concept is not familiar, I invite you that read “Ten Terms of the Data Engineering Ecosystem”. Also, share the link to the survey answering and I would like to know your opinion.

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Jorge Mendoza Rivilla

Data Analytics | Management | Football Analytical | AI | I Write to Understand