Reference - EDB Postgres® AI Lakehouse
HCP Lakehouse is a powerful tool for running analytical queries on your data. It's built on top of Postgres, so you can use your existing Postgres knowledge and tools.
To get the best experience with Lakehouse, follow the quick start to query benchmarking data. Then you can try loading your own data and query the delta lake tables.
This section details some of the important things to know:
- Benchmarking datasets
- Queries in Lakehouse
- Delta Table tools
- DirectScan and fallback modes
- Users
- Loading data
- PGAA functions
For information on the PGFS functions for managing storage location, see the AI Factory PGFS documentation.
Benchmarking datasets
Benchmarking datasets available for Lakehouse
Queries
Supported queries in Lakehouse and best practices when composing them.
Delta Lake Table tools
Tools for working with Delta Lake Tables.
DirectScan
Lakehouse is fastest when it can "push down" your entire query to DataFusion. This explains how to check if your query is running in DirectScan mode.
Managing Users
Managing users in Lakehouse.
Functions
Reference for the functions provided by the PGAA extension
Functions
Reference for the functions provided by the PGAA extension
Supported AWS instances
Supported AWS instances for Lakehouse
Could this page be better? Report a problem or suggest an addition!