Why does every object need a match field?

The Pipedrive API has no upsert. Renta searches for the record first and then updates the hit or creates a new one, so it needs to know which column identifies the record. That is what the record-matching block answers.

Can I match on the Pipedrive ID?

Only in **Update** mode. Creating a record from an internal id is meaningless, so Renta rejects that combination in **Upsert** and **Mirror** before the pipeline is saved.

A row was synced twice and I got two records. Why?

Pipedrive's search index lags a few seconds behind writes. A run started immediately after another can search before the first run's record is indexed and create a duplicate. Scheduled runs are far outside that window.

Does Renta create custom fields in Pipedrive?

No. It reads the fields your account already has and offers them in the mapping block. Create the field in Pipedrive first, then map to it.

What happens to a record when its row leaves the data model?

Nothing, unless the pipeline runs in **Mirror** mode with the deleted-rows policy set to **Delete**. A deleted record goes to the Pipedrive trash and is recoverable for 30 days.

Can Renta create the person a lead belongs to?

No. A lead has to reference a person or an organization that already exists in Pipedrive, so map **Person ID** or **Organization ID** and make sure the parent record is there.

Pipedrive

Renta writes rows from your data warehouse into Pipedrive: persons, organizations, deals, and leads.

Each row becomes one CRM record. Renta looks the record up by the field you nominate, updates it when it finds one, and creates it when it does not, so the same model can keep a segment current instead of piling up duplicates.

Authentication

Renta authenticates with a personal Pipedrive API token. The token carries the permissions of the user it belongs to, so use an account that can see and edit the records you plan to sync.

Connect Pipedrive destination

Go to the CatalogStep 1

Navigate to the Connections > Catalog section in the left sidebar and open the Destinations tab.
Open the Reverse ETL category and click the Pipedrive card.

Pipedrive card in the Reverse ETL category of the Renta destination catalog

Enter the API tokenStep 2

Destination name.
Specify a name for this destination. This is used exclusively in the Renta interface.
API token.
Your personal Pipedrive API token, found in Pipedrive under Settings > Personal preferences > API.

Click Save. Renta verifies the token against your Pipedrive account before storing it, so a wrong or revoked token is rejected here rather than on the first run.

Add a new Pipedrive connection page with the destination name and API token fields

Destination createdStep 3

The new destination appears in the Destinations list with the Active status. You can now use it in Reverse ETL pipelines.

Destinations list with the new Pipedrive destination in Active status

Prepare a data model

A Reverse ETL pipeline reads from a data model: a SQL query saved in the Data models section that decides which warehouse rows to sync and what each row holds. Build it before the pipeline, because the mapping dropdowns are filled from its columns.

Give every row the column you will match on and the fields Pipedrive needs to create the record. For persons that is a name, for deals and leads a title.

-- Contacts prepared for Pipedrive persons.
-- The query returns rows only, no table is created.
WITH demo_persons AS (
  SELECT
    'james.miller@example.com'  AS email,
    'James Miller'              AS name,
    '+12125550101'              AS phone
  UNION ALL SELECT 'olivia.johnson@example.com','Olivia Johnson','+13125550102'
  UNION ALL SELECT 'william.davis@example.com', 'William Davis', '+12145550103'
)
SELECT * FROM demo_persons

Create the data model

Write the queryStep 1

In the left sidebar, open Data models and click New model. Then:

Source.
Choose the warehouse connection the query runs against.
Write your model query.
Paste your SQL. Keep SQL query as the query type.
Run preview.
Check the rows and column names before moving on.

Choose Reverse ETL only as the scope, then click Next step.

Data source step with the SQL editor holding the contact query and the preview results

Confirm the columns and pick the keyStep 2

Review the columns Renta read from the query and mark the one that identifies a row. Pick the column you will also match on in Pipedrive, such as the email, so a changed row keeps updating the same record.

Name the model on the last step and click Create model. The name is what you pick from the Data model dropdown when you build the pipeline.

Schema step with the three columns of the contact model and the unique key marked on email

Create a Pipedrive pipeline

The destination and the data model have to exist before you start.

Select your warehouseStep 1

In the left sidebar, click New pipeline. On the Source step, switch the toggle to Reverse ETL and pick your data warehouse, such as Google BigQuery.

Select a source step with the Reverse ETL toggle and the Google BigQuery card

Select the warehouse connectionStep 2

Choose the warehouse connection that holds your data models and click Next step.

Select your Google BigQuery connection step with the warehouse connections listed

Select Pipedrive as the destinationStep 3

On the Destination step, select Pipedrive under Already connected and click Next step.

Select a destination step with Pipedrive listed under Already connected

Select the destination connectionStep 4

Choose the Pipedrive connection you created earlier and click Next step.

Select your Pipedrive connection step with the available connections listed

Pipeline configuration

On the final step, choose which Pipedrive object the rows become and how Renta recognises a record it has already written.

What Renta sends

Pick the object and the data model.

Pipedrive pipeline settings with the object selection and the data model dropdown

Object	Description
Persons	Contacts. Match on email, name, phone, or the Pipedrive ID.
Organizations	Companies. Match on name or the Pipedrive ID.
Deals	Deals in a pipeline. Match on title or the Pipedrive ID.
Leads	Leads in the Leads Inbox. Match on title or the Pipedrive ID.

Data model chooses the rows to sync. The columns available for matching and mapping below come from it.

Record matching

Tell Renta which column identifies the record. Pipedrive has no upsert of its own, so every object is written by searching first and then updating or creating, and this is the field that search runs on.

The left dropdown offers the unique key of the data model, and the right one offers the match fields the selected object supports. Renta also writes the matched value into the record it creates, so the next run finds it instead of creating a second one.

Pipedrive ID is available only in Update mode. A record cannot be created from an internal id, so pairing it with Upsert or Mirror stops the pipeline from being saved.

Field mapping

Connect warehouse columns to Pipedrive fields. Renta pre-selects the field the object cannot be created without, and the list holds both the standard fields and the custom fields your account already has.

Mapping data model columns to Pipedrive person fields

Object	Required field
Persons	Name
Organizations	Name
Deals	Title
Leads	Title, plus Person ID or Organization ID

A lead has to belong to a person or an organization that already exists in Pipedrive. Renta does not create the parent record, so map Person ID or Organization ID to a column holding an id that is already there.

Renta never creates custom fields. Create the field in Pipedrive first and it appears in this list. A monetary field also needs its currency mapped, otherwise Pipedrive cannot tell what the amount is denominated in and Renta asks for it before saving.

Sync behavior

Decide how a matched record is written and what happens to one whose row disappears, then name the pipeline.

Sync mode and deleted-rows policy dropdowns with the integration name field

Sync mode How a row is written.

Mode	Description
Upsert	Update the matched record, or create it when there is no match. The default.
Update	Update matched records only. A row with no match is rejected instead of creating anything.
Mirror	Upsert the rows that are present and apply the deleted-rows policy to the ones that left the model.

When a source row is deleted What happens to a record whose row is gone. This only acts in Mirror mode.

Option Description
Ignore Leave the Pipedrive record untouched. This is the default.
Delete Delete the record. It lands in the Pipedrive trash and stays recoverable for 30 days.
Integration name.
The name of your pipeline. Edit it to match your preferences.

Option	Description
Ignore	Leave the Pipedrive record untouched. This is the default.
Delete	Delete the record. It lands in the Pipedrive trash and stays recoverable for 30 days.

Schedule

Choose how often the pipeline runs.

Schedule type	Description
Manual	The pipeline runs only when triggered manually through the interface or via API.
Daily	The pipeline runs once a day at the specified update time.
Interval	The pipeline runs at specified time intervals.
Cron Expression	The pipeline runs on a schedule defined by a cron expression.

For Daily schedules, set the Update time (the exact time each run starts), then click Create pipeline.

Renta also supports API triggers and integration with external orchestrators such as Apache Airflow, Dagster, and Prefect. See the full scheduling documentation for details.

The new pipeline appears in the Pipelines section under the Reverse ETL tab, where you can track its runs and progress.

Reverse ETL pipelines list with the new Pipedrive integration

Sync strategy

Renta syncs incrementally. A run compares the data model against the state the previous run recorded and sends only what moved, so a nightly sync touches a handful of records rather than the whole list. The first run has nothing to compare against and delivers the model in full.

Row state	What Renta does
New	Searches by the match field, then updates the record it finds or creates one. In Update mode a row with no match is rejected.
Changed	Writes the new values onto the matched record.
Unchanged	Sends nothing.
Deleted	Follows the deleted-rows policy, which only acts in Mirror mode: leaves the record alone, or deletes it.

Limits

Every write costs a search.
Pipedrive has no upsert, so each row is a lookup followed by a write. Renta keeps the two within separate request budgets because Pipedrive rate-limits its Search API far more tightly than the rest, but a large first run still takes noticeably longer than an incremental one.
The search index lags a few seconds.
A record created moments ago may not be findable yet, so a run started immediately after another can duplicate it. Scheduled runs sit far outside that window.
Custom fields have to exist first.
Renta maps to the fields your account already has and never creates them.
Leads need an existing parent.
A lead is rejected unless it references a person or an organization that is already in Pipedrive.
A run stops when rejections pile up.
Renta halts the run when more than 30% of a batch, or more than 10% of the rows delivered so far, come back rejected. Records already written stay, and the next run picks up where this one stopped.

Frequently asked questions

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