The Jaccard similarity is a simple calculation that determines how similar two sets are, created by botanist Paul Jaccard in 1901. It's calculated as the ratio of the cardinality of the intersection to the cardinality of the union of the two sets. Redis, with its Set data structure, can be used to calculate this similarity using set operations such as union and intersection. However, storing the results of these operations can lead to performance issues, especially if the resulting sets are large. To avoid this, alternative approaches can be taken, but they come with tradeoffs. The Jaccard similarity can be calculated using Redis Set commands or Lua scripts, allowing for more control over the calculation and its performance implications.