Time series data has distinct characteristics, storage requirements, and workloads that differ from relational data, making it unsuitable for traditional relational databases like Postgres or MySQL. Relational databases are designed to maintain accurate records of objects and relationships, whereas time series data tells the story of what's happening now. Time series databases like InfluxDB are purpose-built to handle the unique demands of time series data, offering low latency, flexibility, and advanced analytics capabilities. By recognizing these differences and using a time series database, developers can avoid common pitfalls such as slow write speeds, schema rigidity, and high storage requirements, making it easier to work with time series data effectively.