Serving 100,000 feature vectors per second with Tecton and DynamoDB
Blog post from Tecton
Tecton is a feature store designed to serve real-time data to machine learning models, enabling online inference capabilities such as fraud detection and personalized recommendations. It serves features at low latency, even under high loads, and provides scalability for large-scale ML organizations. Tecton's architecture includes Feature Views, On Demand Feature Views, and Feature Services, which interact with a control plane and DynamoDB to serve data. The system achieves low latency and high availability, meeting its stated SLA targets, and is built to scale further with additional stores like Redis.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Real-time | 3 | 1,043 | 346 | 121 | -9% |
| Kubernetes | 1 | 1,283 | 186 | 74 | -8% |
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