USE CASES

DVT is the fastest path from raw operational data to business insights. Here's how teams use it to cut costs, own their data, and ship analytics faster.

1

CLOUD REPATRIATION

Bring your data home

Connect to Snowflake, BigQuery, or Redshift as SOURCES. Load transformed data to your on-premises PostgreSQL, MySQL, or SQL Server as the TARGET. Cut cloud compute costs by 60-80% while keeping full ownership of your data pipeline.

EXAMPLE

A retail company paying $15K/month in Snowflake compute costs uses DVT to extract analytics-ready data back to an on-prem PostgreSQL cluster. Cloud becomes a source, not the platform.

Snowflake (source) → DVT + DuckDB → PostgreSQL on-prem (target)
2

HYBRID ANALYTICS

Best of both worlds

Keep operational data where it lives — on-prem MySQL, Oracle, SQL Server. Join it with cloud warehouse data from Snowflake or Databricks. DuckDB federates the query locally. No data leaves your network unless you want it to.

EXAMPLE

A hospital system joins on-prem Oracle EHR data with Snowflake claims analytics. Patient data never leaves the on-prem network — only aggregated insights materialize to the cloud.

Oracle on-prem + Snowflake cloud → DuckDB federation → Target of choice
3

REPLACE ENTERPRISE ETL

Own your pipeline

Eliminate Informatica, Talend, SSIS, or DataStage licenses. DVT does the same job with SQL you already know — no GUI, no per-connector fees, no vendor lock-in. One open-source tool replaces a $50K-500K/year license.

EXAMPLE

A manufacturing company replaces their Informatica PowerCenter installation (12 connectors, $200K/year) with DVT. Same data flows, SQL instead of visual mappings, 19 adapters included.

Any source → DVT (SQL models) → Any target
4

MULTI-CLOUD CONSOLIDATION

End vendor lock-in

Sources scattered across BigQuery, Snowflake, and Redshift? DVT federates across all three into one unified target. Switch cloud providers without rewriting your pipeline. Your SQL models are engine-agnostic.

EXAMPLE

A SaaS company with acquisitions has data in BigQuery (marketing), Snowflake (finance), and Redshift (product). DVT consolidates all three into a single PostgreSQL analytics database.

BigQuery + Snowflake + Redshift → DVT → Unified target
5

STARTUP DATA STACK

Full ELT on a laptop

Start with zero cloud costs. PostgreSQL + DuckDB + DVT gives you a complete ELT stack on your laptop. Build your data models, test locally, and scale to cloud when revenue justifies it. No $500/month Fivetran bills on day one.

EXAMPLE

A 3-person startup builds their entire analytics pipeline on a MacBook. PostgreSQL for storage, DVT for transformation, Metabase for dashboards. Total cost: $0/month.

CSV/API → DVT seed → PostgreSQL → DVT models → Dashboard
6

ANALYTICS ENGINEERING

dbt + any source

Already using dbt? DVT extends your project to reference sources beyond your warehouse. Add MySQL operational data, Oracle ERP data, or S3 files — without changing your existing models. Same ref(), same source(), same everything.

EXAMPLE

A data team using dbt with Snowflake needs to join CRM data from an on-prem MySQL instance. Instead of building a separate Fivetran pipeline, they add the MySQL source to their DVT project and write one SQL model.

Existing dbt project → Add DVT → Reference any source
7

DATA LAKE OFFLOAD

Build a lake without Spark

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

EXAMPLE

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

Any database → DVT → S3/GCS as Delta/Parquet
8

ON-PREM BI ACCELERATION

Dashboards in minutes

Connect to ANY operational database — ERP, CRM, POS, MES. Transform with SQL. Materialize insights tables optimized for Tableau, Power BI, or Metabase. Incremental updates mean dashboards refresh in minutes, not hours.

EXAMPLE

A distribution company connects DVT to their Oracle ERP, MySQL POS system, and SQL Server inventory. Business analysts get a single PostgreSQL database with clean, joined, incremental fact tables. Power BI dashboards update every 15 minutes.

Oracle + MySQL + SQL Server → DVT → PostgreSQL → Power BI