Redis offers several probabilistic data structures - Bloom filters, cuckoo filters, Count-Min Sketches, Top-K data structures, and HyperLogLogs - to quickly process large datasets with some loss of precision. These data structures are used in various applications such as Google Chrome's URL filtering, IP address tracking, and network traffic monitoring. They provide fast lookups, efficient storage, and can be used to estimate the frequency of items in a dataset. The choice of which probabilistic data structure to use depends on the specific requirements of the application, including the desired level of precision and the trade-off between accuracy and space usage.