Skip to content
Database ⇄ Human resources

Jdbc to Success Factors integration — real-time, two-way sync

Keep Jdbc 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 Jdbc and Success Factors

Put your workforce data where your apps can reach it: Jdbc 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. Jdbc is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: EmpJob, EmpCompensation, Foundation Objects (FODepartment, FOLocation, FOCostCenter), Position in Success Factors need to exist as queryable Stored procedures & functions, Sequences, Tables, Views in Jdbc 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 Stored procedures & functions, Sequences, Tables, Views in Jdbc with EmpJob, EmpCompensation, Foundation Objects (FODepartment, FOLocation, FOCostCenter), Position 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 Incrementally sync a high-volume table by polling an updated_at or auto-increment column, keeping a downstream store fresh without full reloads.
  • 02 Consolidate several databases from different vendors into one relational store by syncing each through its own JDBC driver.
  • 03 Push new hires (PerPerson, EmpEmployment, EmpJob) into an ERP or payroll system so account, cost-center, and payroll setup fire on hire instead of manual Integration Center exports.
  • 04 Replicate EmpCompensation and EmpJob effective-dated history into a warehouse for headcount, attrition, and compensation reporting without CSV pulls.

Common sync patterns

Reporting and analytics on current data

EmpJob, EmpCompensation, Foundation Objects (FODepartment, FOLocation, FOCostCenter), Position replicate into Jdbc where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.

Org and structure stay aligned

Groups, departments, managers, and reporting lines from Success Factors stay consistent in Jdbc, so hierarchy-driven logic and permissions don't drift.

Computed and operational fields flow back

Values assembled or corrected in Jdbc write onto the matching record in Success Factors where those fields are writable, keeping the people system enriched.

What you can sync between Jdbc 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.

Jdbc objects Success Factors objects How this pairing syncs
Views Stored SELECT queries exposed like tables; read-only projections synced outbound when raw base tables should not be exposed downstream. 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 Jdbc and EmpCompensation to Success Factors — each maps to any object or custom field on the other side.
Columns Per-table fields with data types, nullability, and defaults; enumerated via DatabaseMetaData.getColumns to auto-generate and type-check field mappings. 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. Columns is specific to Jdbc and Foundation Objects (FODepartment, FOLocation, FOCostCenter) to Success Factors — each maps to any object or custom field on the other side.
Primary keys & indexes Key and index definitions read via DatabaseMetaData; the primary key is required for reliable upserts, and indexes on the cursor column keep incremental polling fast. Position Position Management records for headcount and requisition planning; synced with an ATS or ERP to keep positions and reqs aligned. Primary keys & indexes is specific to Jdbc and Position to Success Factors — each maps to any object or custom field on the other side.
Schemas & catalogs Namespaces that group tables and views; the connector targets a schema/catalog and lists its objects from the JDBC metadata to build the sync. PerEmail and PerPhone Contact sub-entities under PerPerson; synced two-way with a directory or comms system to keep worker contact data current. Schemas & catalogs is specific to Jdbc and PerEmail and PerPhone to Success Factors — each maps to any object or custom field on the other side.
Stored procedures & functions Server-side routines callable via JDBC CallableStatement; invoked for custom read or write logic when a table-level mapping is not enough. 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. Stored procedures & functions is specific to Jdbc and User to Success Factors — each maps to any object or custom field on the other side.
Sequences Server-generated identity values; relevant when writing rows into tables whose keys are assigned by the database rather than the source system. PerPerson Person-level container in Employee Central holding biographical data; effective-dated child entities (PerPersonal, PerEmail, PerPhone) hang off it. Sequences is specific to Jdbc and PerPerson to Success Factors — each maps to any object or custom field on the other side.

How changes propagate between Jdbc 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.

Jdbc Success Factors Interval-based propagation

DetectionStacksync polls Jdbc for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.

DeliveryEach detected change is written to Success Factors through its API, with automatic retries and rate-limit backoff.

Success Factors Jdbc 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 Jdbc as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Jdbc: No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.
  • 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 Jdbc ⇄ Success Factors

Connect Jdbc and Success Factors for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jdbc–Success Factors connection.

Real-time

Two-way sync

Changes in Jdbc or Success Factors instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jdbc 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 Jdbc or Success Factors record.

Observability

Monitoring

Track your Jdbc ⇄ 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 Jdbc and Success Factors.

How the Jdbc and Success Factors connectors work

Jdbc

Integration surface
JDBC API (java.sql / javax.sql) executing SQL through a JDBC driver, typically a pure-Java Type 4 driver; reaches any relational database with a driver - PostgreSQL, MySQL, SQL Server, Oracle, IBM DB2, and others - via a JDBC URL such as jdbc:postgresql://host:5432/db.
Authentication
A database user's username and password supplied in the JDBC connection (DriverManager or a DataSource), typically over a TLS/SSL-encrypted connection. Some drivers add Kerberos, integrated Windows auth, or cloud IAM-token auth, but the available methods depend on the target database and its driver.
Change detection
No native change feed. Incremental sync polls a cursor column - an updated_at timestamp or an auto-incrementing key - to pull new and changed rows; detecting deletes needs soft-delete flags or database triggers writing to a shadow table. No webhooks.
Capabilities
read · write
Rate limits
No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.

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 Jdbc 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.

  1. 01

    Connect your apps

    Authenticate Jdbc 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Jdbc connected
    Success Factors connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Jdbc 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Jdbc ⇄ Success Factors
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Jdbc Success Factors
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Jdbc and Success Factors integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 431 integrations available for Jdbc and Success Factors.

Popular · 8 of 431
All Jdbc integrations All Success Factors integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own