Chronon supports a variety of data sources and aims to provide low-latency streaming. We built Chronon to relieve a common pain point for ML practitioners...
Chronon requires ML practitioners to define their features only once, powering both offline flows for model training as well as online flows for model inference.
Chronon accomplishes this by distinguishing between batch features and streaming features. Batch features are calculated daily; streaming features are used for real-time updates...
Work on Chronon does not end with its open-sourcing, with the goals of lowering the cost of iteration and computation even further, making it easier for practitioners to define features...
[
add
]
[
|
|
...
]