Time-Series Database vs Relational Database
Having the right dataset will save you a lot of time and effort. Furthermore, it will allow you to make informed decisions. A data analyst's job is to suggest the best database to use in different situations. Time-series databases (TSDBs) and relational databases (RDBMSs) have well-documented application cases and user bases which means that they also have well-documented differences. For instance, TSDBs can insert a huge volume of data like 1M+ inserts per second. This, however, is not possible with an RDBMS. There is no SQL support with TSDBs, but RDBMSs have full SQL support. TSDBs save storage and calculation costs, but they don't offer solutions that aren't now available. The RDBMS has served the industry well for a long time and is still fully functional.
Data reflects the current state of an entity in an RDBMS and are generally used for:
- Content management systems
- Storing transactional data
- Data that needs to be updated over time
- Long-term storage
TSDBs, on the other hand, are generally used for:
- Monitoring systems over time
- Analytical and reporting data processing
- Append-only changes
- Short-lived data sets