Redis Tutorial

Redis, developed in 2009, is a flexible, open-source, key value data store. Following in the footsteps of other NoSQL databases, such as Cassandra, CouchDB, and MongoDB, Redis allows the user to store vast amounts of data without the limits of a relational database. Additionally, it has also been compared to memcache and can be used, with its basic elements as a cache with persistence. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. Redis is written in c.

Why Redis is different compared to other key-value stores?

Redis is a different evolution path in the key-value DBs where values can contain more complex data types, with atomic operations defined on those data types.

Redis is an in-memory but persistent on disk database, so it represents a different trade off where very high write and read speed is achieved with the limitation of data sets that can’t be larger than memory. Another advantage of in memory databases is that the memory representation of complex data structures is much simpler to manipulate compared to the same data structure on disk, so Redis can do a lot, with little internal complexity.

Redis Data Types
Redis has five data types: Strings, Sets, Sorted Sets, Lists, Hashes


Strings are Redis’ most basic data type.

Some common commands associated with strings are:

SET: sets a value to a key

GET: gets a value from a key

DEL: deletes a key and its value

INCR: atomically increments a key

INCRBY: increments a key by a designated values

EXPIRE: the length of time that a key should exist (denoted in seconds)

Strings can be used to store objects, arranged by key.


If you want to combine strings, you can do that with REDIS sets, a collection of unordered strings.

Some common commands for Sets are:

SADD: Add one or members to a set

SMEMBERS: Get all set members

SINTER: Find the intersection of multiple sets

SISMEMBER: check if a value is in a set

SRANDMEMBER: Get a random set member

Sets can be helpful in a variety of situations. Because each member of a set is unique, adding members to a set does not require a “check then add” operation. Instead the set will check whether the item is a duplicate whenever a SADD command is performed.

Sorted Sets

Sorted sets have an intuitive name: they are a collection of strings associated with a number and are arranged by default in order of least to greatest.

This datatype works well with ranges, and, because they are ordered from the outset, adding, remove, or updating values can be done quickly.

Some common commands for Sorted Sets are:

ZADD: Adds members to a sorted set

ZRANGE: Displays the members of a sorted set arranged by index (with the default low to high)

ZREVRANGE: Displays the members of a sorted set arranged by index (from high to low)

ZREM: Removes members from a sorted set


Lists in Redis are a collection of ordered values. This is in contrast to Sets which are unordered. You can add elements to the beginning or end of a list (even when there are over ten million elements in the list) with great speed.

Some common commands associated with Lists are:

LPUSH: Add a value to the begining of a list

RPUSH: Add a value to the end of a list

LPOP: Get and remove the first element in a list

RPOP: Get and remove the last element in a list

LREM: Remove elements from a list

LRANGE: Get a range of elements from a list

LTRIM: Modifies a list so leave only a specified range


Hashes in Redis are a useful tool to represent objects with many fields. They are set up to store vast amount of fields in a small amount of space. A hash can store more than 4 billion field-value pairs.

Some common Hash commands are:

HMSET: Sets up multiple hash values

HSET: Sets the hash field with a string value

HGET: Retrieves the value of a hash field

HMGET: Retrieves all of the values for given hash fields

HGETALL: Retrieves all of the values for in a hash

One Thought on “Redis Tutorial

  1. ANKIT YADAV on December 30, 2016 at 8:08 pm said:

    Great article sir, i have looking for data structure implementation on the web. this is surely a good tutorial.

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