How does the Pipedrive to PostgreSQL connection work?

Kondado uses a direct integration to extract data from your Pipedrive account via API and load it into your PostgreSQL database. You authenticate your Pipedrive data source once, then select which of the 16 available pipelines to replicate. The platform handles schema creation and data type mapping automatically, ensuring your sales data arrives in PostgreSQL ready for analysis.

What Pipedrive data can I replicate to PostgreSQL?

You can replicate 16 different pipelines including Deals, Persons, Organizations, Activities, Activity Types, and Deal Fields. Each pipeline contains specific fields such as deal values, contact emails, organization names, and activity due dates. This gives you access to 235 fields covering your entire sales operation from lead management to deal closure.

How often does Pipedrive data update in PostgreSQL?

Updates occur on a configurable schedule that you set based on your reporting needs, ranging from every 5 minutes to daily intervals. Near-real-time updates ensure your SQL queries and custom dashboards reflect current sales activities. You can adjust the frequency anytime to balance data freshness with processing requirements.

Can I combine Pipedrive data with other sources in PostgreSQL?

Yes, PostgreSQL serves as a central repository where you can blend Pipedrive sales data with information from additional data sources. You might join deal records with marketing data from other platforms or financial data from accounting systems. This unified view enables comprehensive analysis across your entire business operation.

What format does Pipedrive data take in PostgreSQL?

Each Pipedrive pipeline becomes a separate table in your PostgreSQL database with appropriate column names and data types. Kondado automatically maps Pipedrive fields to PostgreSQL-compatible formats, handling dates, currencies, and text fields correctly. The structured schema supports complex joins and aggregations for building custom sales reports.

Can I send Pipedrive data to PostgreSQL and BigQuery simultaneously?

Yes, Kondado allows you to replicate the same Pipedrive pipelines to multiple destinations including PostgreSQL and BigQuery at different schedules. You might send detailed historical data to PostgreSQL for complex analysis while streaming recent deals to BigQuery for large-scale processing. This flexibility ensures the right data reaches the right analytics environment for each use case.

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Send Pipedrive Data to PostgreSQL Automatically

To send Pipedrive data to PostgreSQL, you need a direct integration that extracts your sales records and loads them into your database without manual exports. Kondado provides a no-code solution that connects your Pipedrive account to PostgreSQL in minutes, allowing you to replicate deals, contacts, and activities on a configurable schedule. You can consolidate sales metrics from multiple pipelines into a single PostgreSQL instance, enabling complex SQL analysis and custom reporting. Simply authenticate your Pipedrive data source, configure your PostgreSQL destination, and select which pipelines you want to replicate. The platform handles the data transfer automatically, updating your database every 5 minutes, hourly, or daily based on your business needs, ensuring your analytics always reflect current sales performance.

Kondado replicates data from 16 Pipedrive pipelines including Deals, Persons, Organizations, and Activities directly to PostgreSQL on a configurable schedule ranging from 5 minutes to daily, requiring no coding or manual CSV exports.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Available Pipedrive Pipelines for PostgreSQL

Replicate your Deals and Deals Flow pipelines to track sales performance evolution directly in PostgreSQL, enabling you to calculate conversion rates and pipeline velocity using custom SQL queries. By combining Persons and Organizations data with Activities, you can build comprehensive customer interaction histories that power advanced segmentation models and churn prediction. This structured data in PostgreSQL supports custom dashboards in Looker Studio or Power BI, allowing you to blend Pipedrive metrics with financial data from other sources for complete revenue analysis and forecasting.

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Pipedrive data available for PostgreSQL

available pipelines

235

extractable fields

Available integrations

Integration	Description
Activities	Unique identifiers, activity types, and due dates are among the fields available for managing tasks, calls, and meetings.
Activity Fields	Fields such as name, data type, and whether the field is editable are essential for defining metadata of custom activities.
Activity Types	Different types of activities, such as tasks and meetings, are categorized to facilitate management and organization.
Deal Fields	Fields such as value, status, and creation date are fundamental for managing deals and their associated information.
Deal Products	Information about products associated with deals, including identifiers and quantities, is essential for sales tracking.
Deals	Data such as unique identifiers, titles, and values are used to manage and track the progress of deals.
Deals Flow (History)	History of changes in deals, including status and values, provides insights into the progress and evolution of sales.
Notes	Notes linked to deals, people, or organizations include fields such as content, creation date, and unique identifiers.
Organization Fields	Field definitions such as name, type, and status are crucial for managing information about organizations.
Organizations	Data such as unique identifiers, names, and status are used to manage and categorize organizations in the system.
Persons	Includes fields such as id, name, and email, enabling management of contacts and associated information.
Products	Contains information on id, name, and price, facilitating management of the product portfolio.
Sales Pipelines	Presents data on id, name, and stages, allowing visualization of the sales flow.
Stages	Includes fields such as id, name, and order, defining the stages of the sales process.
Teams	Provides data on id, name, and members, facilitating organization and management of teams.
Users	Includes information such as id, name, and email, allowing management of users and their permissions.

Activities

Unique identifiers, activity types, and due dates are among the fields available for managing tasks, calls, and meetings.

Activity Fields

Fields such as name, data type, and whether the field is editable are essential for defining metadata of custom activities.

Activity Types

Different types of activities, such as tasks and meetings, are categorized to facilitate management and organization.

Deal Fields

Fields such as value, status, and creation date are fundamental for managing deals and their associated information.

Deal Products

Information about products associated with deals, including identifiers and quantities, is essential for sales tracking.

Deals

Data such as unique identifiers, titles, and values are used to manage and track the progress of deals.

Deals Flow (History)

History of changes in deals, including status and values, provides insights into the progress and evolution of sales.

Notes

Notes linked to deals, people, or organizations include fields such as content, creation date, and unique identifiers.

Organization Fields

Field definitions such as name, type, and status are crucial for managing information about organizations.

Organizations

Data such as unique identifiers, names, and status are used to manage and categorize organizations in the system.

Persons

Includes fields such as id, name, and email, enabling management of contacts and associated information.

Products

Contains information on id, name, and price, facilitating management of the product portfolio.

Sales Pipelines

Presents data on id, name, and stages, allowing visualization of the sales flow.

Stages

Includes fields such as id, name, and order, defining the stages of the sales process.

Teams

Provides data on id, name, and members, facilitating organization and management of teams.

Users

Includes information such as id, name, and email, allowing management of users and their permissions.

See all available data →

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How to send Pipedrive data to PostgreSQL

Sync data automatically — no code, no manual exports.

Connect Your Pipedrive Data Source

Authenticate your Pipedrive account in Kondado by providing your API credentials through the connection interface. Select the specific pipelines you want to replicate, such as Deals, Persons, or Activities.

Configure PostgreSQL Destination

Enter your PostgreSQL connection details including host, database name, and credentials to establish the target location for your sales data. Kondado automatically tests the connection to ensure your database is ready to receive Pipedrive records.

Select Pipelines and Schedule

Choose which of the 16 available Pipedrive pipelines to replicate and set your update frequency from 5 minutes to daily based on your reporting requirements. Once activated, Kondado begins replicating data automatically according to your configuration.

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