Handle millions of feature requests per second with single-digit-msec latencies
Get real-time ML inference with millisecond-latency feature retrieval at scale. Skip the caching layers, eliminate bottlenecks, and avoid inference delays that lead to stale or suboptimal predictions. ScyllaDB delivers consistent speed your ML pipelines require, without the complexity or cost overhead.
Deliver more relevant and accurate recommendations at scale
Reduce false positives and negatives and shift to a more predictive stance
Identify, characterize, and respond to multiple factors for dynamic pricing & risk predictions
Reduce unplanned downtime, improve asset longevity, and lower maintenance costs
CREATE TABLE feature_store (
car_id uuid,
feature_name text,
feature_value text,
PRIMARY KEY (car_id, feature_name)
);
ScyllaDB is plug-and-play with the Feast reference architecture. See how you can integrate your ScyllaDB Cloud database with Feast as an online store.
Join our webinar to build real-time ML apps with Python, Feast, and ScyllaDB.