← All Use Cases

DATA LAKE OFFLOAD

Build a lake without Spark

Materialize models to S3, GCS, or Azure as Parquet or CSV. Build a data lake from any source without Spark infrastructure, EMR clusters, or Databricks workspaces. DVT + Sling handles the heavy lifting.

REAL-WORLD EXAMPLE

A media company exports cleaned analytics tables from PostgreSQL to S3 as Parquet. Downstream teams query with Athena or Trino. No Spark cluster needed.

DATA FLOW

Any database → DVT → S3/GCS as Parquet

WHAT ENABLES THIS

BUCKET STORAGES →

S3, GCS, and Azure are first-class targets — models materialize as objects

SEEDS TO BUCKETS →

dvt seed --target s3_lake loads files straight into the lake as parquet

PYTHON MODELS →

API and ML outputs land in the lake through the same pipeline

RELATED USE CASES

CLOUD REPATRIATION

Bring your data home

MULTI-CLOUD CONSOLIDATION

End vendor lock-in

Sound like your situation? You can have the first model running today.

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