How to store time-series data in MongoDB, and why that’s a bad idea

TimescaleDB outperforms MongoDB in time-series data storage by 260% in insert performance, up to 54x faster queries, and simpler implementation. TimescaleDB uses 10x less disk space than both MongoDB methods, with a hybrid row/columnar storage approach that enables efficient compression of time-series data. While MongoDB's document format is more flexible, SQL-based TimescaleDB provides better developer experience and query performance for complex queries, making it the clear choice for time-series workloads.