Keys at root level having a common prefix can be queried optimally
SCANKEYS/SCANKVS/KEYS/KVS commands returns the results in sorted order
Unlike Redis SCAN(opens in a new tab), Treds SCAN always returns count number of data if data is there
Unlike Redis ZRANGEBYLEX(opens in a new tab), Treds ZRANGELEX always returns data irrespective of score, basically data across different scores are returned
It has Sorted Maps instead of Sorted Sets. So we can create a Sorted Key/Value pair with associated with a score
New command - DELPREFIX - Deletes all keys having a common prefix and returns number of keys deleted
Currently, it only has Key/Value store, Sorted Maps store, List store, Set store and Hash store and only supports strings/number as values
Why is it cool? What is it about TFA that interests you? What does it do that other resources have not done? Does it help you think about the problem in a different way?
I've always been fascinated with the perfect squares, and various patterns that arise from observing them. I love how the article examines the patterns and then extrapolates the study of the patterns to a tool for memorization.
Keys at root level having a common prefix can be queried optimally
SCANKEYS/SCANKVS/KEYS/KVS commands returns the results in sorted order
Unlike Redis SCAN(opens in a new tab), Treds SCAN always returns count number of data if data is there
Unlike Redis ZRANGEBYLEX(opens in a new tab), Treds ZRANGELEX always returns data irrespective of score, basically data across different scores are returned
It has Sorted Maps instead of Sorted Sets. So we can create a Sorted Key/Value pair with associated with a score
New command - DELPREFIX - Deletes all keys having a common prefix and returns number of keys deleted
Currently, it only has Key/Value store, Sorted Maps store, List store, Set store and Hash store and only supports strings/number as values