Analytics
pg-warehouse
Local-first analytics pipeline
pg-warehouse keeps the pipeline close to PostgreSQL and the developer workflow close to SQL. It is designed for teams who want analytics and feature generation without spinning up an oversized stack.
CLI examples
Sync source data
pg-warehouse syncPull incremental PostgreSQL state into the local warehouse.
Run a feature transform
pg-warehouse run --file features.sqlMaterialize a reproducible SQL transform or feature pipeline.
Export outputs
pg-warehouse export --format parquetPublish warehouse outputs for downstream analytics or model training.
What it does
A focused workflow, not a generic platform pitch
Each product page follows the same template so the navigation scales while the content stays readable.
Moves PostgreSQL data into an analytics-friendly local workflow.
Runs repeatable SQL transforms for feature generation and reporting.
Exports outputs to Parquet so downstream systems stay simple and portable.
Architecture diagram
pg-warehouse in the stack
Dark, monospace, and direct. The point is legibility, not decoration.
PostgreSQL
Transactional source of truth and CDC event stream
Sync Layer
Incremental ingestion into local analytics storage
DuckDB + SQL
Transform, model, and generate analytical outputs
Parquet + Features
Portable datasets for BI, ML, and downstream jobs
Key features
What makes this product useful in practice
The feature list stays product-specific while reusing the same card language across the site.
Local-first execution
Build and validate transformations without waiting on remote warehouse cycles.
Feature-ready outputs
Shape raw events into model features or reusable analytics tables.
Minimal moving parts
Use SQL and filesystems instead of a large orchestration surface area.
Postgres to Parquet path
Export clean datasets that stay easy to move across teams and tools.
Use cases
Where teams get leverage
Simple, concrete use cases are more credible than broad category claims.
Feature engineering
Generate model features from operational PostgreSQL data without warehouse sprawl.
Embedded analytics
Build fast internal reporting pipelines for product and operations teams.
Data product prototyping
Move from SQL idea to shipped dataset quickly while staying portable.
GitHub plus consulting
A clean split between GitHub evaluation and consulting rollout
Each repo should be useful on its own, with Burnside consulting available when teams want help turning it into a production workflow.
Open source
Core sync and transform workflows
DuckDB-powered local execution
Simple export patterns for small teams
Consulting
Team governance, scheduling, and deployment patterns
Advanced lineage, auditability, and support
Shared environments for multi-product data teams
Call to action
Start building with pg-warehouse
Review the repo, then bring Burnside in when you want help applying it to a real PostgreSQL environment.