Redis (Remote Dictionary Server )is an in-memory data structure store, used as a distributed, in-memory key–value database, cache and message broker, with optional durability. Redis supports different kinds of abstract data structures, such as strings, lists, maps, sets, sorted sets, HyperLogLogs, bitmaps, streams, and spatial indexes. The project is developed and maintained by a project core team and as of 2015 is sponsored by Redis Labs.
The Redis project began when Salvatore Sanfilippo, nicknamed antirez, the original developer of Redis.
Redis is one of the most powerful in-memory database to server greater End user Experience with hight through put in a real time scenario . Many Organisations has already adopted in the fast growing Digital World .
An In-Memory Open Source Database, supporting a variety of high performance operational, analytics or hybrid use case
An In-Memory Multi-Model Database built on top of open source Redis
Redis – (REmote DIctionary Server) • Open source in-memory database • Key-value store with data structures • Created by Salvatore Sanfilippo (circa 2009) – Source: https://github.com/antirez/redis – Project: redis.ioRedis Enterprise software can be deployed in multiple options .Below diagrams listed all the ways that we can implement based on the organisation infa availability
Redis can be download and installed on VM’s,Can install on Container platforms And also As-A-Service with Cloud platforms like Amazon,Azure and goole cloud . More clouds to add soon as an offering .
Redis can be managed with one of the below offerings .
– Secure Management UI
– Administrative CLI utility
– REST API
How Redis is different from other In Memory DB’s
It’s a data structure store: • Works as a memory store and database • Fast read/write performance • Scales up and out • Transactional • Persistent • Extensible • Small footprint Redis Building Blocks are the Data Structures shown on the below screen .
Why Redis –> Because it give better performance , Uses Simple Data Structures and has Extensible modules to give extra power
Redis secrecy of performance
• Written in C
• Single-threaded and lock free
• Data served entirely from memory
• Commands operate on data structures, respond in milliseconds and can be pipelined
Redis cluster performance with the no of nodes shown in the below table
Redis simplicity
• Developers can use familiar data structures • Operations execute at database level – not the application • With a key/value store, there is no need to work with relational tables and complex SQL statements • Each data type offers simple commands to operate on them • Your database code is cleaner and and more performantRedis Extensibility: Redis Modules Extend Redis Infinitely
• Add-ons that use a Redis API to seamlessly support additional use-cases and data structures
• Modules turn Redis into a Multi-Model database
• Modules still enjoy Redis’ simplicity,
extreme performance, scalability, resiliency and high-availability
• Leverage existing data structures or introduce new ones
• Redis Enterprise Modules are tested and certified by Redis Labs.Redis Multi-Model DataBase
Redis as a simple cache and how it excels the performance
The Problem • Multiple database calls create impossibly slow web page response times | Why Redis Excels • Strings are key/value pairs • SET saves session variables • GET retrieves values |
Redis supports Strings and caching
• Strings store text, which might be made from the results of multiple database queries and HTML
• Support expiry
• Register to listen for changes on keys
and operations
• Multiple eviction policies supported
> SET userid:1 “<HTML></HTML>”
> GET userid:1
> EXPIRE userid:1 60
> DEL userid:1
jedis.set("userid:1", “<HTML></HTML>");
jedis.get("userid:1");
jedis.expire("userid:1", 60);
jedis.del("userid:1");
Redis supports as a Session store
The Problem Maintain session state across multiple servers Multiple session variables High speed/low latency required | Why Redis Excels Hashes are sets of field-value pairs (similar to a Python dictionary, Java Map, etc.) HSET saves variables as fields HMGET retrieve multiple values HINCRBY increments integer fields HDEL deletes a field |
Redis Hashes and Session Storage
hash key: usersession:1
| userid | 8754 |
| name | dave |
| ip | 10:20:104:31 |
| hits | 2 |
| lastpage | home |
> HSET usersession:1 userid 8754 name dave ip 10:20:104:31 hits 1
> HMGET usersession:1 userid name ip hits
> HINCRBY usersession:1 hits 1
> HSET usersession:1 lastpage “home”
> HGET usersession:1 lastpage
> HDEL usersession:1 lastpage
> DEL usersession:1Note: Hashes store a mapping of keys to values – like a dictionary or associative array
Redis can be used as a Queue
The Problem •Tasks need to be processed async to reduce block/wait times •Assign items to worker process and remove from queue at the same time •Similar to buffering high speed data-ingestion • High speed/low latency required | Why Redis Excels • Lists are value queues • LPUSH, RPUSH add values to beginning or end of queue • RPOPLPUSH pops an item from one queue and pushes it to another |
- > LPUSH queue1 orange
- > LPUSH queue1 green
- > LPUSH queue1 blue
- > RPUSH queue1 red
RPOPLPUSH pops a value from one list and pushes it to another list
Redis as a Recommendation Engine
The Problem -People who read this article also read these other articles -Want real-time, not data mining Also used for: -Recommending similar purchases -Identifying fraud | Why Redis Excels • SETS are collections of unique strings – great for tagging! • SADD adds tags to each article • SISMEMBER checks if an article has a given tag • SMEMBERS gets all article tags • SINTER finds similar articles with the same tags |
Set: tag:1 –>
| article 1 | article 3 | …. |
Set: tag:2
| article 3 | article 4 | .rticle 22 | … |
Set: tag:3
| article 2 | article 3 | article 9 | … |
Redis as a Leaderboard Store
The Problem • MANY users playing a game or collecting points • Display real-time leaderboard • Who is your nearest competition? • Disk-based DB is too slow | Why Redis Excels • Sorted Sets associated set elements with a score • ZADD adds/updates a score • ZRANGE, ZREVRANGE gets users in score ranges • ZRANK gets a users rank instantantly |
Redis as a Geo Locator
The Problem • Give me all the pharmacies within a 2 km radius • How far am I from the hospital? | Why Redis Excels • GeoSet stores location as a Geohash • GEOADD adds a location • GEODIST gets distance • GEORADIUS gets locations within a given radius |
Redis Geospatial Indexes for Geolocation
--------------------------------------------------------
> GEOADD pharmacies -0.310392 51.456454 "Charles Harry Pharmacy"
> GEOADD pharmacies -0.296402 51.462069 "Richmond Pharmacy"
> GEOADD pharmacies -0.318604 51.455338 "St Margaret's Pharmacy"
> GEORADIUS pharmacies -0.30566239999996014 51.452921 600 m WITHDIST WITHCOORD ASC
1) 1) "Charles Harry Pharmacy"
2) "511.6979"
3) 1) "-0.31039327383041382"
2) "51.45645288459863309"Redis as a Pub/Sub Message Bus
The Problem • IoT device sending sensor information to multiple services • App sending out messages about activities to multiple users | Why Redis Excels • Pub/Sub broadcasts messages to subscribed listeners • PUBLISH sends messages • SUBSCRIBE gets messages |
Redis as a Time Series Repository
The Problem • IoT device sending sensor information on several metrics • Need to show the metrics in graphs for visualization | Why Redis Excels • Streams collects messages in an efficient queue structure • XADD store messages • XRANGE retrieve messages |