How are time-series databases optimized for temporal data?

Time-series databases (InfluxDB, TimescaleDB, Prometheus) optimize for high-volume timestamped data. Optimizations: column-oriented storage, time-based partitioning (automatic retention), compression (delta, XOR for floats, dictionary for strings), write batching, downsampling/aggregation, specialized indexes (time range). Query patterns: time ranges, aggregations, latest values. Schema: measurement + tags (indexed) + fields. Hot/cold data tiering. Regular data expiration. Consider cardinality limits.