Redis : A high-speed database, cache, and message broker

What is Redis?

• Redis or Remote Dictionary Server , is an open-source NoSQL datastore , advanced key-value store is a fast data store, cache, and even lightweight message broker..
• As of February 2020, Redis is the most popular key-value datastore, according to DB-Engines ranking.
• It is often referred to as a data structure server, since the keys can contain strings, hashes, lists, sets and sorted sets.
• It is written in C.
• It is highly scalable and performance-oriented system.

Redis Data Structures

• String : One the most versatile of Redis building blocks . It can store any kind of data — string , integer , JPEG image , serialized RUBY object , or anything else you want it to carry.
• Set : Redis Sets data structure stores a unique set of members . With Sets , you can add , fetch , or remove members , check membership , or retrieve a random member.
• List : Lists holds collections of string elements sorted according to their order of insertion . Push or pop items from both ends , read individual or multiple items, or find or remove items by value and position.
• Hash : Similar to documents store or row in a relational database , the Redis Hashes structure stores a set of field-value pairs.

How does Redis work?

All Redis data resides in-memory, in contrast to databases that store data on disk or SSDs. By eliminating the need to access disks, in-memory data stores such as Redis avoid seek time delays and can access data in microseconds. Redis features versatile data structures, high availability, geospatial, Lua scripting, transactions, on-disk persistence, and cluster support making it simpler to build real-time internet scale apps.

Redis Vs Memcached

Both Redis and MemCached are in-memory, open-source data stores. Memcached, a high-performance distributed memory cache service, is designed for simplicity while Redis offers a rich set of features that make it effective for a wide range of use cases. For more detailed feature comparision to help you make a decision, view Redis vs Memcached. They work with relational or key-value databases to improve performance, such as MySQL, Postgres, Aurora, Oracle, SQL Server, DynamoDB, and more.

Benefits of Redis

In-memory data store

All Redis data resides in the server’s main memory, in contrast to databases such as PostgreSQL, Cassandra, MongoDB and others that store most data on disk or on SSDs. In comparison to traditional disk based databases where most operations require a roundtrip to disk, in-memory data stores such as Redis don’t suffer the same penalty. They can therefore support an order of magnitude more operations and faster response times. The result is — blazing fast performance with average read or write operations taking less than a millisecond and support for millions of operations per second.

Flexible data structures

Unlike simplistic key-value data stores that offer limited data structures, Redis has a vast variety of data structures to meet your application needs. Redis data types include:

• Strings — text or binary data up to 512MB in size
• Lists — a collection of Strings in the order they were added
• Sets — an unordered collection of strings with the ability to intersect, union, and diff other Set types
• Sorted Sets — Sets ordered by a value
• Hashes — a data structure for storing a list of fields and values
• Bitmaps — a data type that offers bit level operations
• HyperLogLogs — a probabilistic data structure to estimate the unique items in a data set

Simplicity and ease-of-use

Redis simplifies your code by enabling you to write fewer lines of code to store, access, and use data in your applications. For example, if your application has data stored in a hashmap, and you want to store that data in a data store — you can simply use the Redis hash data structure to store the data. A similar task on a data store with no hash data structures would require many lines of code to convert from one format to another. Redis comes with native data structures and many options to manipulate and interact with your data. Over a hundred open source clients are available for Redis developers. Supported languages include Java, Python, PHP, C, C++, C#, JavaScript, Node.js, Ruby, R, Go and many others.

Replication and persistence

Redis employs a primary-replica architecture and supports asynchronous replication where data can be replicated to multiple replica servers. This provides improved read performance (as requests can be split among the servers) and faster recovery when the primary server experiences an outage. For persistence, Redis supports point-in-time backups (copying the Redis data set to disk).

High availability and scalability

Redis offers a primary-replica architecture in a single node primary or a clustered topology. This allows you to build highly available solutions providing consistent performance and reliability. When you need to adjust your cluster size, various options to scale up and scale in or out are also available. This allows your cluster to grow with your demands.

Extensibility

Redis is an open source project supported by a vibrant community. There’s no vendor or technology lock in as Redis is open standards based, supports open data formats, and features a rich set of clients.

Popular Redis Use Cases

Caching

Redis is a great choice for implementing a highly available in-memory cache to decrease data access latency, increase throughput, and ease the load off your relational or NoSQL database and application. Redis can serve frequently requested items at sub-millisecond response times, and enables you to easily scale for higher loads without growing the costlier backend. Database query results caching, persistent session caching, web page caching, and caching of frequently used objects such as images, files, and metadata are all popular examples of caching with Redis.

Chat, messaging, and queues

Redis supports Pub/Sub with pattern matching and a variety of data structures such as lists, sorted sets, and hashes. This allows Redis to support high performance chat rooms, real-time comment streams, social media feeds and server intercommunication. The Redis List data structure makes it easy to implement a lightweight queue. Lists offer atomic operations as well as blocking capabilities, making them suitable for a variety of applications that require a reliable message broker or a circular list.

Gaming leaderboards

Redis is a popular choice among game developers looking to build real-time leaderboards. Simply use the Redis Sorted Set data structure, which provides uniqueness of elements while maintaining the list sorted by users’ scores. Creating a real-time ranked list is as easy as updating a user’s score each time it changes. You can also use Sorted Sets to handle time series data by using timestamps as the score.Session storeRedis as an in-memory data store with high availability and persistence is a popular choice among application developers to store and manage session data for internet-scale applications. Redis provides the sub-millisecond latency, scale, and resiliency required to manage session data such as user profiles, credentials, session state, and user-specific personalization.

Rich media streaming

Redis offers a fast, in-memory data store to power live streaming use cases. Redis can be used to store metadata about users’ profiles and viewing histories, authentication information/tokens for millions of users, and manifest files to enable CDNs to stream videos to millions of mobile and desktop users at a time.

Machine Learning

Modern data-driven applications require machine learning to quickly process a massive volume, variety, and velocity of data and automate decision making. For use cases like fraud detection in gaming and financial services, real-time bidding in ad-tech, and matchmaking in dating and ride sharing, the ability to process live data and make decisions within tens of milliseconds is of utmost importance. Redis gives you a fast in-memory data store to build, train, and deploy machine learning models quickly.

Real-time analytics

Redis can be used with streaming solutions such as Apache Kafka and Amazon Kinesis as an in-memory data store to ingest, process, and analyze real-time data with sub-millisecond latency. Redis is an ideal choice for real-time analytics use cases such as social media analytics, ad targeting, personalization, and IoT.

Important links:

https://www.tutorialspoint.com/redis/index.htm

https://docs.spring.io/spring-data/data-redis/docs/current/reference/html/#reference