Nothing unique. Any database can store "time-series" data. If you look at InfluxDB (key/value) or TimescaleDB (relational), they offer things like high precision time values, higher compression algorithms that work better with timestamps, utilities to make it easier to query for time (buckets, timezones, gap-filling), automatic rollups and aggregations, data deletions based on time, etc.
You can do all that yourself on Redshift but they just offer more built-in functionality for it.
Exactly what mani says. For many people, Redshift, or just plain Postgres, is good enough. But if you find yourself wresting with poor performance, slow queries, high costs, or just an annoying developer experience, I'd encourage you to look at time-series databases (eg TimescaleDB, where I work).
You can do all that yourself on Redshift but they just offer more built-in functionality for it.