Which database is better for handling time-series data: Postgresql or MySQL?

Both PostgreSQL and MySQL are popular open-source databases that are capable of handling time-series data. However, there are some key differences between the two that may make one more suitable than the other depending on your specific needs.

PostgreSQL has some unique features that make it particularly well-suited for time-series data. For example, it has a specialized data type called timestamp with time zone that makes it easy to work with data across different time zones. It also has support for range types and window functions that are useful for analyzing time-series data. Additionally, PostgreSQL has excellent support for indexing, which can greatly improve query performance.

MySQL, on the other hand, is known for its speed and scalability. It has a simple architecture that allows it to handle high-volume workloads with ease. However, it does not have the same level of support for time-series data that PostgreSQL does.

In summary, if you are working with complex time-series data and require advanced features for analysis, PostgreSQL may be the better choice. On the other hand, if speed and scalability are your primary concerns and your time-series data is relatively straightforward, MySQL may be the better option.