Real-time
Two-way sync
Changes in Postgres Heroku or Success Factors instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Human resources
Postgres Heroku to Success Factors integration — real-time, two-way sync
Keep Postgres Heroku and Success Factors in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Postgres Heroku and Success Factors
Put your workforce data where your apps can reach it: Postgres Heroku and Success Factors share the same people, positions, and org structure in real time.
Success Factors is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. Postgres Heroku is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: PerEmail and PerPhone, User, PerPerson, EmpEmployment in Success Factors need to exist as queryable Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases in Postgres Heroku before an app can act on them. When that bridge is a nightly export or a hand-run CSV, every downstream system spends the day working from a roster that has already moved on.
Stacksync syncs Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases in Postgres Heroku with PerEmail and PerPhone, User, PerPerson, EmpEmployment in Success Factors field by field, in real time. You decide which system owns which fields — Success Factors typically owns identity and org attributes, while operational or computed values can flow back the other way — and Stacksync keeps every copy consistent, matching records on a stable key and resolving conflicts by rules you set.
The result is one live picture of the workforce on both sides: HR keeps its source of truth, and the database keeps a current mirror that internal apps, reports, and access controls can trust without a batch window in between.
Common use cases
- 01 Keep several Heroku app databases aligned with one system of record
- 02 Reflect billing and subscription records into the app database so product logic reads local rows
- 03 Write updated PerEmail, PerPhone, and User attributes back into SuccessFactors from an identity or directory system so contact data stays current.
- 04 Two-way sync of User and EmpJob (position, department, manager, cost center) into Postgres so provisioning, internal apps, and analytics read current org data in SQL while HR edits in SuccessFactors.
Common sync patterns
Computed and operational fields flow back
Values assembled or corrected in Postgres Heroku write onto the matching record in Success Factors where those fields are writable, keeping the people system enriched.
Mirror people records into the database
Records maintained in Success Factors land as queryable Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases in Postgres Heroku, so internal apps and dashboards read live data instead of a periodic export.
One directory of record
When a person record is added, changed, or deactivated in either system, the matching row in the other stays current, ending dual maintenance.
What you can sync between Postgres Heroku and Success Factors
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| Postgres Heroku objects | Success Factors objects | How this pairing syncs | |
|---|---|---|---|
| Views Read-side projections exposed to outbound syncs. | EmpCompensation Effective-dated pay and compensation; usually read into a warehouse for reporting, writable for comp updates as new dated slices. | Views is specific to Postgres Heroku and EmpCompensation to Success Factors — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed result sets synced outward on refresh. | Foundation Objects (FODepartment, FOLocation, FOCostCenter) Org-structure master data (department, location, cost center, division); mastered elsewhere and written in, or read out to build org charts. | Materialized Views is specific to Postgres Heroku and Foundation Objects (FODepartment, FOLocation, FOCostCenter) to Success Factors — each maps to any object or custom field on the other side. | |
| Schemas Namespaces that scope which tables a sync reads and writes. | Position Position Management records for headcount and requisition planning; synced with an ATS or ERP to keep positions and reqs aligned. | Schemas is specific to Postgres Heroku and Position to Success Factors — each maps to any object or custom field on the other side. | |
| Primary and Unique Keys Match keys for idempotent upserts from connected systems. | PerEmail and PerPhone Contact sub-entities under PerPerson; synced two-way with a directory or comms system to keep worker contact data current. | Primary and Unique Keys is specific to Postgres Heroku and PerEmail and PerPhone to Success Factors — each maps to any object or custom field on the other side. | |
| JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | User Core identity/User entity behind role-based permissions; a model distinct from Employee Central, synced two-way with a directory or IdP and downstream apps. | JSONB Columns is specific to Postgres Heroku and User to Success Factors — each maps to any object or custom field on the other side. | |
| Sequences Generate surrogate keys for rows created by inbound syncs. | PerPerson Person-level container in Employee Central holding biographical data; effective-dated child entities (PerPersonal, PerEmail, PerPhone) hang off it. | Sequences is specific to Postgres Heroku and PerPerson to Success Factors — each maps to any object or custom field on the other side. |
How changes propagate between Postgres Heroku and Success Factors
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
Postgres Heroku Success Factors Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
DeliveryEach detected change is written to Success Factors through its API, with automatic retries and rate-limit backoff.
Success Factors Postgres Heroku Sub-second propagation
DetectionSuccess Factors notifies Stacksync of record changes through webhook events. Polling on each entity's lastModifiedDateTime / lastModifiedOn (effective-dated entities require date-range handling).
DeliveryEach detected change is applied to Postgres Heroku as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
- Success Factors: OData calls are throttled at the tenant level (Access Limits for OData V2); large reads must be paginated (default page size 1000) via $top/$skip or paging cursors.
What ships with Postgres Heroku ⇄ Success Factors
Connect Postgres Heroku and Success Factors for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Postgres Heroku–Success Factors connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Postgres Heroku or Success Factors data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single Postgres Heroku or Success Factors record.
Observability
Monitoring
Track your Postgres Heroku ⇄ Success Factors sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Postgres Heroku and Success Factors.
How the Postgres Heroku and Success Factors connectors work
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
Success Factors
- Integration surface
- OData V2 and V4 REST APIs (plus legacy SFAPI / Compound Employee SOAP API)
- Authentication
- OAuth 2.0 SAML Bearer Assertion — register an OAuth client for an API key (used as client_id), then exchange a signed SAML assertion for a short-lived access token; legacy HTTP Basic auth is being retired
- Change detection
- Polling on each entity's lastModifiedDateTime / lastModifiedOn (effective-dated entities require date-range handling); Intelligent Services can also push a fixed set of standard business events (e.g. Employee Hire) to a REST endpoint
- Capabilities
- read · write · webhooks
- Rate limits
- OData calls are throttled at the tenant level (Access Limits for OData V2); large reads must be paginated (default page size 1000) via $top/$skip or paging cursors.
How it works
How to connect Postgres Heroku to Success Factors — three steps, no code
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
- 01
Connect your apps
Authenticate Postgres Heroku and Success Factors with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Postgres Heroku
connected
Success Factors
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Postgres Heroku and Success Factors objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
objects · Postgres Heroku ⇄ Success FactorsCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Postgres Heroku Success FactorsCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Postgres Heroku and Success Factors integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Postgres Heroku and Success Factors: authenticate both systems, choose the objects to sync (such as Postgres Heroku's Views and Materialized Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Postgres Heroku and Success Factors connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Postgres Heroku–Success Factors integration in-house.
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Yes — Stacksync ships production-grade connectors for both Postgres Heroku and Success Factors. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. On Success Factors: Polling on each entity's lastModifiedDateTime / lastModifiedOn (effective-dated entities require date-range handling); Intelligent Services can also push a fixed set of standard business events (e.g. Employee Hire) to a REST endpoint. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Postgres Heroku side: Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases, plus custom fields where Postgres Heroku exposes them. On the Success Factors side: PerEmail and PerPhone, User, PerPerson, EmpEmployment. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
SECURITY
Security teams trust Stacksync
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
→ SECURITY WITH BENEFITS
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 448 integrations available for Postgres Heroku and Success Factors.
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Postgres Heroku ⇄ Paylocity -
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Postgres Heroku ⇄ BambooHR -
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Success Factors ⇄ OpenSearch -
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No integrations match .
