Connect JustCall to PostgreSQL
Send JustCall contacts, users, calls and 3 more data types to PostgreSQL on a schedule. Filter by date. Refresh as often as every 15 minutes.
PostgreSQL
schema justcall
contactsuserscallssmsphone_numbers- 1 more data type
How to connect JustCall and PostgreSQL
4 steps. You can preview the JustCall data in Coupler.io before anything reaches PostgreSQL.
Step 1 of 4
Connect JustCall
Enter your JustCall API key. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the JustCall data you want in PostgreSQL.
Step 3 of 4
Connect PostgreSQL
Enter your PostgreSQL connection details, then the schema and table for the JustCall data.
Show 3 more fields Show fewer fields
Step 4 of 4
Choose a write mode and schedule
Every run either replaces or appends the data in PostgreSQL. Run it as often as every 15 minutes.
Each run deletes the existing rows in contacts and loads fresh JustCall data.
Coupler.io made it easy to create dashboards and reports from different data sources. The sync is reliable and the user experience is amazing.
Take your data analytics to the next level
Sign Up with Google
Sign Up with MICROSOFT
SIGN UP WITH EMAIL
By signing up to Coupler.io, you agree to our Privacy Policy and Terms of Use.
Build your JustCall integrations with these destinations
Get the most of JustCall to PostgreSQL integration
Gather data
Understand data
Automate data
Act on data
6 data types, including Contacts, Users, Calls, Sms and Phone numbers.
With your JustCall API key, entered once when you add the connection.
Yes. Set the start date to cover the period you need.
Yes, if the database user has CREATE privileges. Coupler.io creates the justcall schema and the contacts table on the first run.
Yes. Append adds new rows to contacts on each run, while Replace swaps in a fresh copy. With Append, add new JustCall columns to the table yourself before the next run.
On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.
Yes. Add more sources to the same data flow, for example Pipedrive or Calendly, and join or append them before the data reaches PostgreSQL.
