Can you integrate Pendo with Postgres Heroku?

Explore a Pendo and Postgres Heroku integration with a Stacksync engineer. Stacksync support for Pendo and Postgres Heroku is not established by the connector documentation reviewed for this page. Start with one record and the update your business needs to identify an implementation path.

Can Pendo and Postgres Heroku sync in both directions?

Confirm two-way support with Stacksync for the records and fields you need in both systems. Access to a vendor API does not confirm that its Stacksync connector supports write-back.

What should be ready before the Pendo and Postgres Heroku initial load?

Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Identify the Pendo account, edition, environment, and business objects the integration must access. Identify the Postgres Heroku account, edition, environment, and business objects the integration must access. Use the pair worksheet to record ownership and acceptance criteria.

How fast does the Pendo to Postgres Heroku sync run?

Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.

Will existing duplicates merge automatically?

No. Stacksync documents that pre-existing duplicates are not merged automatically when two-way sync begins. Review the initial dataset and matching plan before enabling it; an empty destination can simplify the first load.

How do I map Pendo fields to Postgres Heroku?

Start with one business entity and a stable record ID. Map a small set of editable fields with compatible types, test required values and relationships, then expand after the pilot passes.

What should I do if a record fails to sync?

Check the destination error, field constraints, permissions, and current source value. The Stacksync issues dashboard supports retry and revert; retry reads current source values, so verify the intended record state before acting.

What does a Pendo and Postgres Heroku integration cost?

Use the current Stacksync pricing page and confirm the supported implementation with the team. Scope the required objects, record volume, update frequency, initial load, and support needs when comparing a managed connector with native or custom development.

Which records should the Pendo and Postgres Heroku pilot start with?

Start by reviewing Feature Events in Pendo and Proposed event or activity table in Postgres Heroku (choose its name) in Postgres Heroku. Check how these records relate in your workflow, then confirm the actual fields and supported operations. Test record matching and one failed or repeated update before adding more records.

Analytics / Database · Two-way sync platform

Pendo and Postgres Heroku integration

Plan how Pendo and Postgres Heroku should share data across your business. Work with Stacksync engineers on record mapping, system access, and the requirements for running the integration.

Scope your workflow with an integration engineer
Review the systems, records, and updates you need

Integration planning

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Pendo

Postgres Heroku

Review the integration scope

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Case study

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Migrated from Celigo

Migrated from Heroku Connect

Migrated from Matillion

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Migrated from Fivetran

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Migrated from Celigo

Proposed workflow

Event or activity reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting eventA change involving Pendo Feature Events or the proposed event or activity table in Postgres Heroku needs a defined result in the other system.

Start with Pendo Feature Events and the proposed event or activity table in Postgres Heroku. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve the related customer, user, or transaction identity without assuming the event ID is the entity ID.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

What to verifyDeliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.

Review records and field ownership

Proposed record relationships

Records to connect

Use these examples to define record matching and field ownership for your technical review.

Download the mapping worksheet

CSV · No email required

Example record relationships between Pendo and Postgres Heroku
Pendo record	Postgres Heroku record	Record matching	Field ownership
Feature EventsProposed record; confirm Stacksync object support.Reporting dataset	Proposed event or activity tableProposed table; choose its name and schema.	Keep the source event ID, source system, occurrence time, and ingestion time. Use an explicit duplicate-detection key.	Decide whether the destination stores an immutable history or only a current-state summary.
AccountsProposed record; confirm Stacksync object support.Reporting dataset	Proposed company tableProposed table; choose its name and schema.	Retain the source company ID and the destination customer/company ID. Separate legal entities, subsidiaries, and business units; a shared name or web domain is insufficient.	Assign ownership separately for relationship details and finance-controlled billing details.
VisitorsProposed record; confirm Stacksync object support.Reporting dataset	Proposed contact tableProposed table; choose its name and schema.	Use a stable person/contact ID and an explicit cross-system lookup. Email can change and can be shared, so treat it as a matching clue rather than a universal key.	Keep consent and communication preferences under an agreed authority; a general contact update must not silently resubscribe someone.

These relationships do not establish connector availability. Review the required connection and record operations with Stacksync.

Record coverage to review

Use documented coverage where available. Catalog record types are starting points for review and do not confirm Stacksync support.

Pendo

Connection and object support require review

Record types to review with Stacksync

Record types	Coverage and requirements
Visitors Accounts Feature Events Page Events Guide Events Poll / NPS Responses	Confirm support for this record type and the direction you need.

Discuss Pendo requirements

Postgres Heroku

Connection and object support require review

Record types to review with Stacksync

Record types	Coverage and requirements
Tables Views Materialized Views Schemas Primary and Unique Keys JSONB Columns	Confirm support for this record type and the direction you need.

Discuss Postgres Heroku requirements

Connection essentials

Confirm Stacksync support and account requirements for undocumented connections. Interface information alone does not establish connector availability.

View setup requirements and limits

Connection requirement	Pendo	Postgres Heroku
Integration interface	Pendo Engage API (REST) on app.pendo.io (US) / app.eu.pendo.io (EU), base path /api/v1/ - Aggregation API for reads and the Metadata API for writes	SQL wire protocol (standard PostgreSQL)
Authentication	Confirm the credentials, API plan, and permissions required for Pendo.	Confirm the credentials, API plan, and permissions required for Postgres Heroku.
Change detection	Confirm how Stacksync detects changes for this connector and the objects you need.	Confirm how Stacksync detects changes for this connector and the objects you need.
Read access	Confirm with Stacksync	Confirm with Stacksync
Write access	Confirm with Stacksync	Confirm with Stacksync

Enterprise controls

Security and control for your integrations

Explore security controls

Compliance and data transfers

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

Record-level recovery

Inspect sync errors and use retry and revert controls to resolve failed updates.

Read the recovery guide

Implementation

Technical reference

Review setup, record relationships, testing, and recovery for your implementation.

Authentication, permissions and API limits

Connection requirements and limits

Pendo

Integration interface: Pendo Engage API (REST) on app.pendo.io (US) / app.eu.pendo.io (EU), base path /api/v1/ - Aggregation API for reads and the Metadata API for writes
Authentication: Confirm the credentials, API plan, and permissions required for Pendo.
Change detection: Confirm how Stacksync detects changes for this connector and the objects you need.
Read access: Confirm with Stacksync
Write access: Confirm with Stacksync

Setup requirements

Identify the Pendo account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Pendo, including read/write support, authentication, and initial-load limits.

Limitations to check

Confirm Stacksync support for Pendo and the record types your workflow needs.
Review write-back, deletion handling, update timing, and account limits with the integration team.

Postgres Heroku

Integration interface: SQL wire protocol (standard PostgreSQL)
Authentication: Confirm the credentials, API plan, and permissions required for Postgres Heroku.
Change detection: Confirm how Stacksync detects changes for this connector and the objects you need.
Read access: Confirm with Stacksync
Write access: Confirm with Stacksync

Setup requirements

Identify the Postgres Heroku account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Postgres Heroku, including read/write support, authentication, and initial-load limits.

Limitations to check

Confirm Stacksync support for Postgres Heroku and the record types your workflow needs.
Review write-back, deletion handling, update timing, and account limits with the integration team.

Prepare Pendo and Postgres Heroku access

Set up both accounts before testing the mapping. Use test records where available, and identify the account administrator who can approve access and help resolve setup errors.

Pendo setup checklist

Identify the Pendo account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Pendo, including read/write support, authentication, and initial-load limits.

Postgres Heroku setup checklist

Identify the Postgres Heroku account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Postgres Heroku, including read/write support, authentication, and initial-load limits.

Prepare to go live

Record the fields each system can update, the first-load cutoff, both record IDs, the expected update delay, and who handles errors. Complete the tests before production before expanding to more records.

Use the Pendo and Postgres Heroku planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.

Talk to an engineer · Review current pricing

Record identity and field ownership

Use these data-model references to describe the records your connection needs. They are planning examples; connector availability and supported operations must be established before implementation.

Download the mapping worksheet · CSV, no email required

Reporting dataset

Feature Events / Proposed event or activity table in Postgres Heroku (choose its name)

Plan a event or activity dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Pendo: Object support to establish
Postgres Heroku: Your database schema
Record identity: Keep the source event ID, source system, occurrence time, and ingestion time. Use an explicit duplicate-detection key.
Field ownership: Decide whether the destination stores an immutable history or only a current-state summary.

Fields to include

Source event ID
Event type
Occurred-at time
Related record ID
Payload version

Record dependencies: Resolve the related customer, user, or transaction identity without assuming the event ID is the entity ID.
Validation: Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.
Recovery: Identify side effects already completed before replaying an event; use the agreed deduplication key.

Reporting dataset

Accounts / Proposed company table in Postgres Heroku (choose its name)

Plan a company dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Pendo: Object support to establish
Postgres Heroku: Your database schema
Record identity: Retain the source company ID and the destination customer/company ID. Separate legal entities, subsidiaries, and business units; a shared name or web domain is insufficient.
Field ownership: Assign ownership separately for relationship details and finance-controlled billing details.

Fields to include

Source record ID
Legal or display name
Business-unit reference
Lifecycle status

Record dependencies: Resolve parent organizations, business units, and currency references before dependent transactions.
Validation: Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
Recovery: Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.

Reporting dataset

Visitors / Proposed contact table in Postgres Heroku (choose its name)

Plan a contact dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Pendo: Object support to establish
Postgres Heroku: Your database schema
Record identity: Use a stable person/contact ID and an explicit cross-system lookup. Email can change and can be shared, so treat it as a matching clue rather than a universal key.
Field ownership: Keep consent and communication preferences under an agreed authority; a general contact update must not silently resubscribe someone.

Fields to include

Source person ID
Display name
Email address
Organization reference
Consent state

Record dependencies: Resolve the organization relationship and any owner or consent references required by the destination.
Validation: Test an email change, two records sharing an email, and a person associated with multiple organizations.
Recovery: Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.

Compare integration approaches

Choose a method around one example record and the update your business needs. Use Feature Events / Proposed event or activity table in Postgres Heroku (choose its name) to review record matching and confirm Stacksync support for the required operations. Compare ongoing sync, a custom workflow, and a scheduled export against that requirement.

Stacksync managed sync

Best fit: Review compatibility with a Stacksync engineer using an example of the records and updates you need.
Operating responsibility: Fits ongoing record synchronization when the required operations are supported. Add workflow steps for approvals or business actions that go beyond copying fields.
Before you choose: Check record matching: Keep the source event ID, source system, occurrence time, and ingestion time. Use an explicit duplicate-detection key. Verify field coverage, deletion handling, and how changes are detected.

Native vendor integration

Best fit: A vendor-built integration may fit if it supports your Pendo and Postgres Heroku record types.
Operating responsibility: Can reduce setup for a supported workflow. You may need another method for records or business steps it does not cover.
Before you choose: First check whether either vendor offers this integration. If available, verify Feature Events / Proposed event or activity table in Postgres Heroku (choose its name), update direction, account tier, and related-record handling.

Custom API or workflow

Best fit: Consider when Pendo and Postgres Heroku need a transformation, approval, or action outside a direct record sync.
Operating responsibility: Provides control over business steps; the team owns credentials, version changes, error queues, and reconciliation.
Before you choose: Verify endpoint permissions, pagination, quotas, duplicate detection, and failure recovery.

File or scheduled snapshot

Best fit: Consider for a one-time Pendo / Postgres Heroku migration or a reporting need with an explicit freshness window.
Operating responsibility: Can simplify a bounded transfer; later changes and deletion history require another extraction or a separately designed incremental process.
Before you choose: Record the extraction cutoff, source IDs, encoding, date/number formats, and reconciliation totals.

Workflow scenarios and expected results

Event or activity reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting event: A change to the selected Feature Events or Proposed event or activity table in Postgres Heroku (choose its name) record needs a defined result in the other system.

Start with Pendo Feature Events and Postgres Heroku Proposed event or activity table in Postgres Heroku (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve the related customer, user, or transaction identity without assuming the event ID is the entity ID.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.

If it fails: Identify side effects already completed before replaying an event; use the agreed deduplication key.

Company reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting event: A change to the selected Accounts or Proposed company table in Postgres Heroku (choose its name) record needs a defined result in the other system.

Start with Pendo Accounts and Postgres Heroku Proposed company table in Postgres Heroku (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve parent organizations, business units, and currency references before dependent transactions.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.

If it fails: Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.

Contact reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting event: A change to the selected Visitors or Proposed contact table in Postgres Heroku (choose its name) record needs a defined result in the other system.

Start with Pendo Visitors and Postgres Heroku Proposed contact table in Postgres Heroku (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve the organization relationship and any owner or consent references required by the destination.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Test an email change, two records sharing an email, and a person associated with multiple organizations.

If it fails: Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.

Compare Pendo and Postgres Heroku reporting data

This is an evaluation scenario; connector and operation support require confirmation.

Starting event: An analytical result from Pendo must be reconciled with or displayed alongside a selected destination dataset.

Select Visitors or Accounts and record what each row measures, how records are grouped, the timezone, and the reporting cutoff.
Map the analytical entity key to the business record in Postgres Heroku; an aggregate row is not equivalent to an individual transaction.
If an output will be written back, name its owner and carry a computation timestamp so stale results can be recognized.

Expected result: Totals compare the same time window and level of detail; late-arriving data produces a traceable revision rather than an unexplained overwrite.

If it fails: Recompute the selected window and check entity mapping before sending the result again.

Initial load and acceptance testing

Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.

Feature Events / Proposed event or activity table in Postgres Heroku (choose its name)

Test case

Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.

Expected result

The expected event or activity relationship is preserved with no duplicate action or unintended write.

Accounts / Proposed company table in Postgres Heroku (choose its name)

Test case

Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.

Expected result

The expected company relationship is preserved with no duplicate action or unintended write.

Visitors / Proposed contact table in Postgres Heroku (choose its name)

Test case

Test an email change, two records sharing an email, and a person associated with multiple organizations.

Expected result

The expected contact relationship is preserved with no duplicate action or unintended write.

Direction and permissions

Test case

Bring an example source record and the intended destination operation to the compatibility review. Confirm the supported route before granting write access.

Expected result

Only an approved, supported direction and permitted fields are written.

Freshness and reconciliation

Test case

Measure source and destination times for the selected records under normal load and a burst. Reconcile IDs and values using the same filters and cutoff.

Expected result

The process meets its agreed freshness target and reconciliation has no unexplained differences.

Failed updates, retries and recovery

Start with the failed record and the destination error, then inspect the source value, field requirements, and access.

Rejected or repeated event or activity change

Investigate

Inspect Pendo Feature Events and Postgres Heroku Proposed event or activity table in Postgres Heroku (choose its name), their IDs, and the destination error.

Next action

Identify side effects already completed before replaying an event; use the agreed deduplication key.

Rejected or repeated company change

Investigate

Inspect Pendo Accounts and Postgres Heroku Proposed company table in Postgres Heroku (choose its name), their IDs, and the destination error.

Next action

Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.

Rejected or repeated contact change

Investigate

Inspect Pendo Visitors and Postgres Heroku Proposed contact table in Postgres Heroku (choose its name), their IDs, and the destination error.

Next action

Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.

A record type or update is unavailable

Investigate

Check the Pendo and Postgres Heroku connector guides, account permissions, and any operations marked On Request.

Next action

Ask the integration team to confirm a supported way to handle that record. Verify whether it needs connector configuration or a separate workflow step.

Source and destination disagree after a retry

Investigate

Compare current source values, destination validation, identity mappings, and any side effects already completed.

Next action

Stacksync issue retry reads the current source state. Decide the intended state before retrying or reverting; reconcile downstream effects separately.

Read the Stacksync issues dashboard guide for retry and revert behavior.

Change detection and update delivery

How updates move between Pendo and Postgres Heroku

See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.

Pendo Postgres Heroku Direction requires confirmation

Detect changesConfirm how Stacksync detects changes for this connector and the objects you need.

Apply updatesConfirm that Stacksync can create or update the records you need in Postgres Heroku.

Postgres Heroku Pendo Direction requires confirmation

Detect changesConfirm how Stacksync detects changes for this connector and the objects you need.

Apply updatesConfirm that Stacksync can create or update the records you need in Pendo.

Update timing and record limits

Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
Review write-back, deletion handling, update timing, and account limits with the integration team.
Review write-back, deletion handling, update timing, and account limits with the integration team.

FAQ