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SOLUTIONS

Redis for
feature stores

Feature Store Mobile Image

Get the fastest machine learning predictions

How it works

Get ultra-low-latency predictions

Real-time AI apps need immediate responses, and we deliver sub-millisecond predictions. That means we can support the most time-sensitive operations, including fraud detection, dynamic pricing, and recommendation systems where fast decisions and responses are key.

Integrate with existing tech stacks

We work seamlessly with top offline stores, like Tecton and Feast, to integrate into existing ML workflows. This streamlines data management by accessing, storing, and retrieving ML features directly and ensures smooth transitions between storage layers so apps work better and get to production faster.

Reduce downtime

Our five-nines availability and single-digit-second failover are crucial for mission-critical AI apps, delivering data consistency and uninterrupted operations, minimizing downtime, protecting data integrity, and maintaining smooth workflow continuity.

See how our customers use feature store

“It’s not just about putting in a food order. It’s about providing an optimal experience for our customers. It’s really, really fast. Plus it’s a lot cheaper.”

Daniel Galinkin
Head of ML Engineering, iFood

<1ms

millisecond per read

“We also saw a 38% decrease in Redis latencies, helping to improve the runtime performance of serving models.”

Arbaz Khan, DoorDash

38%

decrease in latency

Read more customer stories

Learn more about feature stores

Video

Dec.09.2024

Redis + Amazon SageMaker for real-time fraud detection demo

Watch this video on how you can set up Redis and Amazon SageMaker to detect fraud in real-time. Demo repo is included in the description of the video.

Blog

Apr.07.2022

Feature Stores for Real-time AI/ML: Benchmarks, Architectures, and Case Studies

Read how feature stores support leading-edge machine learning use cases and how the feature store you choose can impact cost and performance.

Video

Nov.10.2022

Using Redis as Online Feature Store for Real-time Inference

Explore how to implement real-time machine learning pipelines using Feast feature store and how Redis enables low latency prediction and scoring.

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