Probabilistic (original) (raw)
Probabilistic data structures in Redis
Probabilistic data structures give approximations of statistics such as counts, frequencies, and rankings rather than precise values. The advantage of using approximations is that they are adequate for many common purposes but are much more efficient to calculate. They sometimes have other advantages too, such as obfuscating times, locations, and other sensitive data.
Probabilistic data structures are available as part of Redis Open Source and they are available in Redis Software and Redis Cloud. SeeInstall Redis Open Source orInstall Redis Enterprisefor full installation instructions.
HyperLogLog is a probabilistic data structure that estimates the cardinality of a set.
Bloom filters are a probabilistic data structure that checks for presence of an item in a set
Cuckoo filters are a probabilistic data structure that checks for presence of an element in a set
t-digest is a probabilistic data structure that allows you to estimate the percentile of a data stream.
Top-K is a probabilistic data structure that allows you to find the most frequent items in a data stream.
Count-min sketch is a probabilistic data structure that estimates the frequency of an element in a data stream.
Redis probabilistic data structures support multiple configuration parameters.