Time-Series Data
IoT, metrics, and logs — specialized storage and query patterns for timestamped data.
Every ten seconds, a temperature sensor writes a reading. Every minute, your application logs its memory usage. Every millisecond, a stock exchange records a trade. These are all time-series data — ordered sequences of measurements indexed by time.
Time-series data has unique characteristics that make it fundamentally different from traditional application data. It's append-heavy (new data constantly arrives, old data rarely changes). It's time-ordered (the timestamp is always the most important dimension). And it grows fast — a single IoT device generating one reading per second produces 2.6 million rows per month.
Traditional relational databases can store time-series data, but they struggle with the volume and query patterns. Specialized tools exist for a reason, and understandin
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