Yes. Snowplow streams raw and enriched behavioral data into Databricks via structured, real-time pipelines, enabling Spark-based processing, ML model training, and advanced AI workloads.
The integration supports both streaming and batch processing modes, allowing teams to leverage Databricks' lakehouse architecture for cost-effective storage and compute.
Snowplow's governed, event-level data provides the high-quality foundation needed for feature engineering, model training, and AI application development within the Databricks environment.
The infrastructure’s dbt integration enables transformation workflows that prepare Snowplow data for Databricks AI/BI tools and machine learning pipelines.
From success stories and architecture deep dives to live events and AI trends — explore resources to help you design smarter data products and stay ahead of what’s next.
Browse our Latest Blog PostsWhether you’re modernizing your customer data infrastructure or building AI-powered applications, Snowplow helps eliminate engineering complexity so you can focus on delivering smarter customer experiences.
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