Redis for Media and Entertainment
Media/Entertainment Apps Change the Game with Redis.
Media and entertainment applications need the impeccable performance and versatility of Redis to deliver unique, delightful customer experiences that are at the heart of these industries.
Media/Entertainment Use Cases for Redis
Unique Redis data structures such as Geo, Hashes, Sorted Sets and its Pub/Sub capability enable incredible flexibility in processing of user data and characteristics like preferences/location to ensure consumers are presented with the right offers, pricing and recommendations.
Redis is not only adept at powering social conversations, ratings, tracking followers and chat but also incredibly powerful for generating instantaneous analytics like scores, ranks, and leaderboards in even massively multiplayer online games.
High Speed Transactions
Game play actions, account authentications, media purchases, content downloads and other transactions in the media and entertainment industry require the impressive performance of Redis, with the controls over consistency and durability provided by Redis enterprise.
Real time analytics
Redis powers the real-time session analysis, behavior-based recommendations, location-based offers, top trending items and spot promotions needed to encourage upsell and cross sell.Redise Flash enables cost-effective real time analytics with even very large datasets.
The Redis-ML module with Redise allows the production deployments of sophisticated machine learning models used for collaborative filtering, or behavior-based classification and targeting, at substantial infrastructure cost savings.
Caching is often the smartest way for media and entertainment providers to serve content like graphics, pictures, thumbnails, music, labels, metadata, tags and more at lightning speeds. Redis’ built-in caching features such as key expiry, keyspace notifications etc enable extreme responsiveness with minimal overhead on expensive disk-based RDBMS databases.
“Redis Labs eliminated the need for Twitch to build operational expertise around managing the nuances of running Redis in production.”