What are Hot and Warm Searches?
The performance of a datastore system is significantly related to how the data is stored for searching. Hot data means that the data is in a position ready to search, while warm means that it resides in a state that is searchable, but not in the fastest memory. When a warm search occurs the data migrates to faster memory, what application programmers call a lazy load. In Fluency, this takes just a couple of minutes, and the search is ongoing at the same time. Follow-on searches will then have the performance of a hot search. Fluency does not use cold for searches in the last 365 days. Cold searches use datastores that require inconvenient wait times, in the manner of hours and days. Amazon AWS Glacier storage is an example of cold storage.