PostgreSQL
Read and write support varies by record
Record types covered in the setup guide
| Record types | Coverage and requirements |
|---|---|
| See connector requirements. Confirm field permissions and sync direction. |
Database / Human resources · Two-way sync platform
PostgreSQL and Success Factors integration
Plan how PostgreSQL and Success Factors 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
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Proposed workflow
Worker or employee reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting eventA change involving the proposed worker or employee table in PostgreSQL or Success Factors PerPerson needs a defined result in the other system.
Start with the proposed worker or employee table in PostgreSQL and Success Factors PerPerson. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve organization, position, manager, and effective-date context before dependent changes.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
What to verifyTest a future-dated transfer, a rehire, concurrent assignments, and an employee with a missing manager.
Review records and field ownershipProposed record relationships
Records to connect
Use these examples to define record matching and field ownership for your technical review.
Download the mapping worksheetCSV · No email required
| PostgreSQL record | Success Factors record | Record matching | Field ownership |
|---|---|---|---|
| Proposed worker or employee tableProposed table; choose its name and schema.Reporting dataset | PerPersonProposed record; confirm Stacksync object support. | Use the worker/employment ID and distinguish a person from their employment records, assignments, or rehires. | HR owns employment decisions and effective dates. Downstream changes must follow the authorized joiner/mover/leaver process. |
| Proposed application user or identity tableProposed table; choose its name and schema.Reporting dataset | UserProposed record; confirm Stacksync object support. | Use the immutable user ID within the tenant or directory. Do not equate an application user with a CRM customer contact. | Identity and application owners approve account lifecycle and access changes; synchronize only approved attributes. |
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.
Success Factors
Connection and object support require review
Record types to review with Stacksync
| Record types | Coverage and requirements |
|---|---|
| Confirm support for this record type and the direction you need. |
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 | PostgreSQL | Success Factors |
|---|---|---|
| Integration interface | SQL wire protocol (PostgreSQL frontend/backend protocol) | OData V2 and V4 REST APIs (plus legacy SFAPI / Compound Employee SOAP API) |
| Authentication | Database credentials | Confirm the credentials, API plan, and permissions required for Success Factors. |
| Change detection | The Postgres connector uses logical replication. | Confirm how Stacksync detects changes for this connector and the objects you need. |
| Read access | Available for supported records | Confirm with Stacksync |
| Write access | Available for supported records | Confirm with Stacksync |
Enterprise controls
Security and control for your integrations
Explore security controlsCompliance 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 guideImplementation
Technical reference
Review setup, record relationships, testing, and recovery for your implementation.
Authentication, permissions and API limits
Connection requirements and limits
PostgreSQL
- Integration interface
- SQL wire protocol (PostgreSQL frontend/backend protocol)
- Authentication
- Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
- Change detection
- The Postgres connector uses logical replication. The separate Postgres Heroku connector uses database triggers when replication rights are unavailable.
- Read access
- Available for supported records
- Write access
- Available for supported records
Setup requirements
- Use a single-column primary key with a database-generated default for every selected table; composite primary keys are not supported.
- Give the connected database role the required ownership and replication rights. Logical replication requires wal_level=logical; check the hosted database procedure before changing it.
- For PostgreSQL 12 and earlier, have the database administrator install the pgcrypto extension before starting the sync so tracking tables can use gen_random_uuid(). PostgreSQL 13 and later provide this function without the extension.
Limitations to check
- Renaming a schema, table, or column requires updating the sync configuration.
- Database views cannot be used as writable destinations in two-way sync; validate the selected connector and view support separately.
Technical documentation
- Amazon Lightsail
- Amazon RDS
- Authorize Postgres
- Basedash
- Cloud SQL
- Digital Ocean
- Ensuring Secure Cloud SQL Connections with SSL Certificate
- Ensuring Secure RDS Connections with SSL Certificate
- Heroku
- Postgres
- Render
- Required Permissions
- Retool
- Snippets
- Supabase
Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.
Success Factors
- Integration interface
- OData V2 and V4 REST APIs (plus legacy SFAPI / Compound Employee SOAP API)
- Authentication
- Confirm the credentials, API plan, and permissions required for Success Factors.
- 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 Success Factors account, edition, environment, and business objects the integration must access.
- Confirm a Stacksync connector or implementation path for Success Factors, including read/write support, authentication, and initial-load limits.
Limitations to check
- Confirm Stacksync support for Success Factors and the record types your workflow needs.
- Review write-back, deletion handling, update timing, and account limits with the integration team.
Prepare PostgreSQL and Success Factors 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.
PostgreSQL setup checklist
- Use a single-column primary key with a database-generated default for every selected table; composite primary keys are not supported.
- Give the connected database role the required ownership and replication rights. Logical replication requires wal_level=logical; check the hosted database procedure before changing it.
- For PostgreSQL 12 and earlier, have the database administrator install the pgcrypto extension before starting the sync so tracking tables can use gen_random_uuid(). PostgreSQL 13 and later provide this function without the extension.
Setup guides: Authorize PostgresEnsuring Secure Cloud SQL Connections with SSL CertificateEnsuring Secure RDS Connections with SSL Certificate
Success Factors setup checklist
- Identify the Success Factors account, edition, environment, and business objects the integration must access.
- Confirm a Stacksync connector or implementation path for Success Factors, 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 PostgreSQL and Success Factors planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.
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
Proposed worker or employee table in PostgreSQL (choose its name) / PerPerson
Plan a worker or employee dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
- PostgreSQL
- Your database schema
- Success Factors
- Object support to establish
- Record identity
- Use the worker/employment ID and distinguish a person from their employment records, assignments, or rehires.
- Field ownership
- HR owns employment decisions and effective dates. Downstream changes must follow the authorized joiner/mover/leaver process.
Fields to include
- Source worker ID
- Employment status
- Effective date
- Manager reference
- Department
- Record dependencies
- Resolve organization, position, manager, and effective-date context before dependent changes.
- Validation
- Test a future-dated transfer, a rehire, concurrent assignments, and an employee with a missing manager.
- Recovery
- Reconcile effective dates before applying a delayed change; route ambiguous termination or access changes for review.
Reporting dataset
Proposed application user or identity table in PostgreSQL (choose its name) / User
Plan a application user or identity dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
- PostgreSQL
- Your database schema
- Success Factors
- Object support to establish
- Record identity
- Use the immutable user ID within the tenant or directory. Do not equate an application user with a CRM customer contact.
- Field ownership
- Identity and application owners approve account lifecycle and access changes; synchronize only approved attributes.
Fields to include
- Source user ID
- Tenant reference
- Account status
- Group references
- Record dependencies
- Resolve tenant and group references and establish a protected administrative-account policy.
- Validation
- Test a renamed login, disabled account, missing group, and a user existing in two tenants.
- Recovery
- Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.
Compare integration approaches
Choose a method around one example record and the update your business needs. Use Proposed worker or employee table in PostgreSQL (choose its name) / PerPerson 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: Use the worker/employment ID and distinguish a person from their employment records, assignments, or rehires. 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 PostgreSQL and Success Factors 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 Proposed worker or employee table in PostgreSQL (choose its name) / PerPerson, update direction, account tier, and related-record handling.
Custom API or workflow
- Best fit
- Consider when PostgreSQL and Success Factors 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 PostgreSQL / Success Factors 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
Worker or employee reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Proposed worker or employee table in PostgreSQL (choose its name) or PerPerson record needs a defined result in the other system.
- Start with PostgreSQL Proposed worker or employee table in PostgreSQL (choose its name) and Success Factors PerPerson. Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve organization, position, manager, and effective-date context before dependent changes.
- 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 a future-dated transfer, a rehire, concurrent assignments, and an employee with a missing manager.
If it fails: Reconcile effective dates before applying a delayed change; route ambiguous termination or access changes for review.
Application user or identity reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Proposed application user or identity table in PostgreSQL (choose its name) or User record needs a defined result in the other system.
- Start with PostgreSQL Proposed application user or identity table in PostgreSQL (choose its name) and Success Factors User. Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve tenant and group references and establish a protected administrative-account policy.
- 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 a renamed login, disabled account, missing group, and a user existing in two tenants.
If it fails: Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.
Worker lifecycle planning for Success Factors and PostgreSQL
This is an evaluation scenario; connector and operation support require confirmation.
Starting event: A worker joins, moves, or leaves in Success Factors; a downstream process in PostgreSQL needs the approved context.
- Identify the worker and employment record represented by User or PerPerson. Retain effective dates and organizational scope.
- Determine what a selected destination dataset represents: an operational task, a user identity, or a reporting row. Define a relationship; do not map these records as if they were the employee itself.
- Require the process owner to approve any access, payroll, or account action and assign an exception owner.
Expected result: Rehires and concurrent assignments keep distinct employment context; delayed updates do not reverse a newer effective state.
If it fails: Inspect employment identity and effective dates before retrying the downstream action.
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.
Proposed worker or employee table in PostgreSQL (choose its name) / PerPerson
Test case
Test a future-dated transfer, a rehire, concurrent assignments, and an employee with a missing manager.
Expected result
The expected worker or employee relationship is preserved with no duplicate action or unintended write.
Proposed application user or identity table in PostgreSQL (choose its name) / User
Test case
Test a renamed login, disabled account, missing group, and a user existing in two tenants.
Expected result
The expected application user or identity 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 worker or employee change
Investigate
Inspect PostgreSQL Proposed worker or employee table in PostgreSQL (choose its name) and Success Factors PerPerson, their IDs, and the destination error.
Next action
Reconcile effective dates before applying a delayed change; route ambiguous termination or access changes for review.
Rejected or repeated application user or identity change
Investigate
Inspect PostgreSQL Proposed application user or identity table in PostgreSQL (choose its name) and Success Factors User, their IDs, and the destination error.
Next action
Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.
A record type or update is unavailable
Investigate
Check the PostgreSQL and Success Factors 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 PostgreSQL and Success Factors
See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.
PostgreSQL Success Factors Direction requires confirmation
Detect changesThe Postgres connector uses logical replication. The separate Postgres Heroku connector uses database triggers when replication rights are unavailable.
Apply updatesConfirm that Stacksync can create or update the records you need in Success Factors.
Success Factors PostgreSQL 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 PostgreSQL.
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.
FAQ
PostgreSQL and Success Factors integration FAQ
-
Explore a PostgreSQL and Success Factors integration with a Stacksync engineer. Stacksync support for Success Factors 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.
-
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.
-
Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Use a single-column primary key with a database-generated default for every selected table; composite primary keys are not supported. Identify the Success Factors account, edition, environment, and business objects the integration must access. Use the pair worksheet to record ownership and acceptance criteria.
-
Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
-
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.
-
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.
-
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.
-
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.
-
Start by reviewing Proposed worker or employee table in PostgreSQL (choose its name) in PostgreSQL and PerPerson in Success Factors. 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.
-
Choose a method around one example record and the update your business needs. Use Proposed worker or employee table in PostgreSQL (choose its name) / PerPerson 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.
Integration directory
Related integrations
Review documented support, sync direction, and setup requirements on each pair page. Search all 545 integrations listed for PostgreSQL and Success Factors.
Next step
Plan your integration with an engineer
Walk through your PostgreSQL and Success Factors records, field mappings, and requirements with an integration engineer.
