Connect Harvest to PostgreSQL
Send Harvest invoices, tasks, companies and 19 more data types to PostgreSQL on a schedule. Filter by date and narrow it down by project status. Refresh as often as every 15 minutes.
harvest
invoicestaskscompanyprojectsusers- 17 more data types
How to connect Harvest and PostgreSQL
6 steps. You can preview the Harvest data in Coupler.io before anything reaches PostgreSQL.
Step 1 of 6
Connect Harvest
Sign in to Harvest and authorize Coupler.io. There's no API key to copy.
Step 2 of 6
Choose what to export
Pick the Harvest data you want in PostgreSQL.
Show 14 more data types Show fewer data types
Step 3 of 6
Fine-tune the export
Optional settings for this Harvest export.
Show 14 more data types Show fewer data types
Show 1 more field Show fewer fields
Step 4 of 6
Narrow it down
Filter Harvest records before they reach PostgreSQL.
Step 5 of 6
Connect PostgreSQL
Enter your PostgreSQL connection details, then the schema and table for the Harvest data.
Show 3 more fields Show fewer fields
Step 6 of 6
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 invoices and loads fresh Harvest data.
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Build your Harvest integrations with these destinations
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22 data types, including Invoices, Tasks, Company, Projects and Users.
You sign in to Harvest and authorize Coupler.io. There's no API key to copy.
Yes. Filter by changed date to load the period you need.
Yes. Available filters include project status. You can also add your own filter conditions.
Yes, if the database user has CREATE privileges. Coupler.io creates the harvest schema and the invoices table on the first run.
Yes. Append adds new rows to invoices on each run, while Replace swaps in a fresh copy. With Append, add new Harvest 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 Clockify or Jira, and join or append them before the data reaches PostgreSQL.