PostgreSQL Automated ETL

ETL the Modern Way. Get your data out of PostgreSQL so you can analyze it.

The Postgres data source allows you to import data from your Postgres databases into Panoply. The data schema of your Postgres source will be ported into Panoply as is. Each record retrieved will also include metadata columns that denote when it was extracted from your Postgres source and when it was last written into your Panoply database.

Modernizing PostgreSQL ETL

What is ETL?

Integrating data for analytics can be especially hard in a fast-shifting, rapid growth startup environment, where relevant business data might be spread out across a collection of apps and spreadsheets. ETL (Extract, Transform, Load) tools will help you collect your data from APIs and file transfers (the Extract step), convert them into standardized analytics-ready tables (the Transform step) and put them all into a single data repository (the Load step) to centralize your analytics efforts.

The shift to ELT

The traditional ETL model is a relic of the pre-cloud era, when compute resources were expensive, and everything needed to be cleaned up before analysis. These days, moving the transformation step closer to the time of analysis is not only feasible, it’s desirable. ELT lets you load raw data, increasing your analytical flexibility and moving relevant data more quickly from your engineering team to your analytics and BI teams.

All in one PostgreSQL data pipeline

Panoply’s 80+ data connectors and built-in automated cloud data warehouse will let you go from a collection of siloed datasets to sophisticated analyses that integrate your PostgreSQL data in a matter of minutes. Panoply is the only tool that combines an ETL process with a data warehouse, giving you total control over your data from sync to storage. We’ll handle all the infrastructure so you can skip the engineering work and go straight to analysis with your favorite BI tool.

PostgreSQL