Zammad to PostgreSQL

Copy (ELT) Zammad data to PostgreSQL in a few clicks and keep it up to date automatically.

How to Replicate Zammad Data to PostgreSQL

Copying Zammad data to PostgreSQL cannot be simpler. You just need to perform the following three simple steps.

Step 1

Specify necessary connection parameters for Zammad.

Step 2

Specify necessary connection parameters for PostgreSQL.

Step 3

Select Zammad objects to replicate.

Powerful Replication Features

Automatic Schema Creation

You don’t need to prepare the PostgreSQL database — Skyvia creates the tables, corresponding to the Zammad objects, in the data warehouse automatically.

Complete or Partial Replication

With Skyvia you can extract and load all the data from a Zammad object or disable loading for some Zammad object fields. You can also configure filters for data to replicate.

Change Data Capture

Skyvia not just copies Zammad data to PostgreSQL once, it can keep your PostgreSQL database up-to-date with Zammad automatically, ensuring you always have fresh data for data analysis without any user intervention.

Optimized Data Loading

Skyvia combines a high-performance optimized batch data loading into PostgreSQL with a granular, per-record data insertion and error logging in case of any errors.

True ETL — Data Import Tool

If you need more than just to copy data from Zammad to PostgreSQL, you may use Skyvia’s powerful ETL functionality for Zammad and PostgreSQL integration. Skyvia’s data import tools will correctly extract Zammad data, transform it, and load to PostgreSQL when PostgreSQL tables have different structure than Zammad objects. Moreover, Skyvia Data Import allows loading data in any direction, supporting Reverse ETL scenario.

Automation and Monitoring

Flexible Scheduling

Use flexible scheduling settings to automate replication

Detailed Logging

You can find detailed logs for each execution in the package Run History.

Email Notifications

Enable email notifications and always know if anything goes wrong.

Integrate Zammad and PostgreSQL with minimal effort and in only a few clicks!