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t-digest: A New Probabilistic Data Structure in Redis Stack

Blog post from Redis

Post Details
Company
Date Published
Author
Lior Kogan
Word Count
2,296
Company Posts That Month
10
Language
English
Hacker News Points
-
Post removed?
No
Summary

The Redis Stack's introduction of t-digest, a new probabilistic data structure, offers an efficient way to estimate percentiles in large datasets. T-digest can be used to answer common questions about data streams and large datasets, including estimating the 50th, 90th, and 99th percentile. The data structure provides sub-millisecond latency, sub-linear memory requirements, and high accuracy, making it suitable for streaming data and huge datasets. With t-digest, users can query statistics such as percentiles, ranks, and trimmed means, allowing them to efficiently analyze and process large amounts of data. Additionally, the Redis Stack's support for t-digest extends its existing functionality, including RedisInsight, search and query, JSON, time series, and probabilistic data structures.

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