When creating applications that store and analyze large amounts of data, such as time series, log data, or event-storing ones, developing a good and future-proof data model can be a difficult task. Determining the most appropriate data types to store the information depends on various factors, including the required precision of float-point values, the content of the values (such as text), compressibility, and query speed.

Choosing the right data types in PostgreSQL can significantly impact your database’s performance and efficiency. In this article, we’ll explore best practices for selecting data types that align with PostgreSQL’s recommendations. Whether you’re designing tables for a new project or optimizing an existing database, these insights will help you make informed decisions.

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