We use the concept of a feature store. We need the engine, and we use Feast as our feature store framework to build our feature store. We use the DuckDB engine as a data engine, which helps us move data from the offline feature store to the online feature store. The online feature store is part of the feature store where we serve our features to the operational environment. We have some daily processes, for example, where we update features in operational environments every hour. For this update, we use DuckDB to load data from Parquet to Redis.
Embedded Databases are lightweight databases integrated into applications, offering efficient data management capabilities without requiring separate database servers. Perfect for IoT devices and mobile apps, these databases ensure fast data processing and minimal latency.Embedded Databases cater to the need for high-performance data storage within embedded systems. They provide seamless integration with host applications, making them ideal for scenarios where space and resource constraints...
We use the concept of a feature store. We need the engine, and we use Feast as our feature store framework to build our feature store. We use the DuckDB engine as a data engine, which helps us move data from the offline feature store to the online feature store. The online feature store is part of the feature store where we serve our features to the operational environment. We have some daily processes, for example, where we update features in operational environments every hour. For this update, we use DuckDB to load data from Parquet to Redis.