Databricks

Databricks pioneered the "Lakehouse" concept. With Delta Live Tables (DLT), it treats streaming data as a first-class citizen. It allows engineers to build declarative pipelines that can switch between batch and streaming with a simple configuration change, all built on Spark.

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Why use it in EDA? It is the best place to perform complex processing and AI on your event streams. If your EDA feeds into Machine Learning models or complex regulatory reporting, Databricks provides the unified environment to handle that logic reliably.

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How do we use it?

• Streaming ETL: Ingesting raw events, cleaning them, and storing them for analysis.‍
• Real-Time AI: Running inference on streaming data to update models live.