Hopsworks Feature Store with

Spark (EMR, Databricks, Cloudera, HDInsight, DataProc)

If you have large volumes of data as input to your feature or batch pipelines, then Spark can be used to compute features as DataFrames and write them directly to Hopsworks Feature Store. Spark can write features in both batch and streaming modes.

Hopsworks Integrations

Spark can be used to implement batch feature pipelines, streaming feature pipelines, batch inference pipelines, and streaming inference pipelines for features that are written to Hopsworks Feature Store.

Other integrations

Modal
Neo4J
Vertex AI

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