Time-series data applications are becoming increasingly popular, leading to a surge in time-series databases. Most of these adopt a NoSQL model due to its scalability benefits over traditional relational databases. However, TimescaleDB takes a different approach by leveraging the power of relational databases and solving the scaling problem. By implementing adaptive time/space chunking, TimescaleDB achieves consistent insert throughput that surpasses vanilla PostgreSQL, resulting in a 15x improvement on insert rates. This approach allows for robust primary and secondary index support while maintaining the full feature set of PostgreSQL.