How does Memcached compare to CDNs
Redis is a great choice for implementing a high availability in-memory cache that reduces data access latency, increases throughput, and reduces the load on your relational or NoSQL database or application. Redis can process frequently requested items with response times of less than a millisecond. Plus, you can easily scale for higher loads without the costly backend getting bigger. The caching of results from database queries, end-to-end sessions, web pages and frequently used elements such as images, files and metadata are popular examples of caching with Redis.
Chat, messaging and queuing
Redis supports Pub / Sub with pattern matching and a variety of data structures such as lists, sorted sentences, and hashes. This allows Redis to support chat rooms, real-time comment streams, social media feeds, and server intercommunication with high performance. The Redis List data structure makes it easy to implement a user-friendly queue. Lists provide atomic operations and blocking capabilities, making them useful for various applications that require a reliable message broker or a circular list.
Redis is a popular option among game developers looking to create real-time leaderboards. Just use the Redis Sorted Set data structure which provides uniqueness of items and maintains the list sorted by points by users. Building a real-time leaderboard is as easy as updating a user's scores with every change. You can also use Sorted Sets to process time series data as points using timestamps.
Redis is a highly available and persistent in-memory data store that is popular with application developers because it can store and manage session data for applications on the Internet. The data store offers latencies of less than a millisecond, scalability and resilience, which are required for the management of session data such as user profiles, login information, session status and user-specific personalization.
Comprehensive media streaming
Redis provides fast in-memory data storage for running live streaming use cases. Redis can also be used to store user profile and viewing history metadata, authentication information and tokens for millions of users, and manifest files to create content delivery networks (CDNs) for streaming video to millions of mobile users - and desktop devices at the same time.
Redis offers specially designed in-memory data structures and operators to manage real-time geospatial data to measure and at high speed. The Redis commands, e.g. B. GEOADD, GEODIST, GEORADIUS and GEORADIUSBYMEMBER, for saving, processing and analyzing geodata in real time, make handling geodata quick and easy. You can use Redis to add location-based features such as travel time, distance and points of interest to your applications.
Modern data-driven applications require machine learning to quickly process large volumes of data, differences and speeds, and to automate decision-making. For use cases such as fraud detection in games and financial services, real-time bidding in ad tech, dating and ridesharing, the ability to process live data and make decisions in under a millisecond is paramount Importance. Redis gives you fast in-memory data storage to quickly build, train, and deploy machine learning models.
In combination with other streaming solutions such as Apache Kafka and Amazon Kinesis, Redis can be used as in-memory data storage to read in real-time data and to process and analyze it with a latency of less than a millisecond. Redis is the ideal choice for real-time analytics use cases like social media analytics, targeted ad serving, personalization, and IoT.
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