This document provides an introduction and overview of Redis. Redis is described as an in-memory non-relational database and data structure server. It is simple to use with no schema or user required. Redis supports a variety of data types including strings, hashes, lists, sets, sorted sets, and more. It is flexible and can be configured for caching, persistence, custom functions, transactions, and publishing/subscribing. Redis is scalable through replication and partitioning. It is widely adopted by companies like GitHub, Instagram, and Twitter for uses like caching, queues, and leaderboards.

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An introduction to Redis
by Romain Francez

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Redis
“An in memory non relational database”
“Memcached but better”
“A data structure server”

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Redis is Simple
● Works out of the box
○ No schema
○ No user
○ Default config works just fine

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Redis is Simple
● Key/Value Store
● Simple operations
○ Usually get/set with variations

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Redis is Flexible
● Data types
○ Bitmaps
○ Hashes
○ HyperLogLogs
■ Probabilistic data structure to estimate the cardinality of a set
■ Memory efficient
○ Keys
■ Yes, also a type
■ Anything binary safe (like the content of an image)
○ Lists
○ Sets
○ Sorted Sets
○ Strings

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Redis is Flexible
● Configuration
○ Store denormalised data you can afford to lose?
■ By default in memory + snapshot on the disk
■ Disable the disk writes
○ Use it as a cache?
■ Use a LRU (Least Recently Used) memory policy

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Redis is Flexible
● Custom functions with lua
● Transactions
○ If you need them
● Pub/Sub
○ Isn’t even related to the key space

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Redis is Scalable
● High Availability with Sentinel
○ Configuration based
● Most operations are O(1)
○ But some have high constant time (See some Hyperloglogs commands)
● Non relational database
○ No problems related to scaling relations across servers
● Partitioning
○ With limitations

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Redis Use Cases
“So basically I can do everything and anything
with Redis?”

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Widely adopted
● GitHub
○ Routing, queue, config management
● Instagram
○ Mapping photos with the user that created them
○ Needs the persistence of data on disk
○ Advanced usage of hashes
● StackOverflow
○ Cache
● Twitter
○ Timeline (tweets ordered by ids), ads
○ On disk features not used
○ Added custom data types
● Your favorite video site
○ Hint: not YouTube
○ Sorted sets and hashes
○ Kept MySQL, but no reads from it: use it to populate Redis

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Other Usages
● Autocomplete
● Search engine
● Distributed locking
● Session management
● Leaderboards

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Leaderboard Example
> ZADD leaderboard 13 "Cold" 22 "Cindy" 7 "mymo" 20 "herrrox" 15
"Dreaty" 4 "cqnqr"
(integer) 6
> ZREVRANGE leaderboard 0 2 WITHSCORES
1) "Cindy"
2) "22"
3) "herrrox"
4) "20"
5) "Dreaty"
6) "15"
> ZRANGE leaderboard 0 0 WITHSCORES
1) "cqnqr"
2) "4"

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Leaderboard Example
> ZINCRBY leaderboard 20 "cqnqr"
"24"
> ZREVRANK leaderboard "cqnqr"
(integer) 0

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Leaderboard Example
> ZCARD leaderboard
(integer) 6
> ZADD leaderboard 7 "BaDy"
(integer) 1
> ZCARD leaderboard
(integer) 7
> ZREM leaderboard "mymo"
(integer) 1
> ZCARD leaderboard
(integer) 6

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Conclusion
● Redis can be used for any of your needs
○ You might have to get into advanced stuff though
● Handles well lots of data

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Thanks
Any questions ?

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