The Redis brand itself is known for Redis… an open source (BSD licensed) in-memory data structure store, used as database, cache and message broker.
Recommendations & predictions
The machine learning element of the new project is focused on so-called real-time ‘recommendations & predictions for interactive apps’, in combination with Spark Machine Learning (Spark ML).
Redis-ML claims to accelerate the delivery of real-time predictive analytics for use cases such as fraud detection and risk evaluation in financial products, product or content recommendations for e-commerce applications, demand forecasting for manufacturing applications or sentiment analyses of customer engagements.
“The Redis-ML module with Apache Spark, delivers lightning fast classifications with larger data sizes, in real-time and under heavy load, while allowing many applications developed in different languages to simultaneously utilise the same models,” states Dvir Volk, senior architect at Redis Labs. “The Redis-ML module is a great demonstration of the power of Redis Modules API in supporting the cutting-edge needs of next generation applications.”
Spark ML (previously MLlib) delivers proven machine learning libraries for classification and regression tasks. Combined with Redis-ML, applications can now deliver precise, re-usable machine learning models, faster and with lower execution latencies.
Redis-ML avoids the need to generate the model from file systems or other disk based data stores, a process which usually involves long serialization/deserialization overheads with slow disk accesses.