Time series databases are optimized to handle typical workloads that involve measuring change over time, such as monitoring weather patterns or CPU usage. These databases store data in a way that allows for efficient querying and analysis of past performance and predicting future outcomes. They can handle both metrics and events, and provide features like automatic lifecycle management and scalability to accommodate growing datasets. Using a time series database can significantly speed up query times, especially when summarizing large periods of time, and some databases also come with built-in visualization tools. Choosing the right time series database is crucial for developers who want to focus on building applications rather than managing architecture.