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Database ⇄ Human resources

Azure SQL Database to Success Factors integration — real-time, two-way sync

Keep Azure SQL Database 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.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Azure SQL Database and Success Factors

Put your workforce data where your apps can reach it: Azure SQL Database 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. Azure SQL Database is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Position, PerEmail and PerPhone, User, PerPerson in Success Factors need to exist as queryable Stored procedures, Change tracking / CDC tables, Tables, Views in Azure SQL Database 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, Change tracking / CDC tables, Tables, Views in Azure SQL Database with Position, PerEmail and PerPhone, User, PerPerson 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 Feed an Azure SQL operational database with orders and inventory from an ERP in near real time.
  • 02 Expose SaaS data (billing, support tickets) as tables in Azure SQL for reporting teams already on Microsoft tooling.
  • 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

Computed and operational fields flow back

Values assembled or corrected in Azure SQL Database 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 Stored procedures, Change tracking / CDC tables, Tables, Views in Azure SQL Database, 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 Azure SQL Database 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.

Azure SQL Database objects Success Factors objects How this pairing syncs
Rows and columns Standard relational records with typed columns; primary keys anchor upserts. EmpJob Effective-dated job info: position, department, manager, FTE, pay grade, cost center; the most-synced record for downstream HR and provisioning. Rows and columns is specific to Azure SQL Database and EmpJob to Success Factors — each maps to any object or custom field on the other side.
Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. EmpCompensation Effective-dated pay and compensation; usually read into a warehouse for reporting, writable for comp updates as new dated slices. Stored procedures is specific to Azure SQL Database and EmpCompensation to Success Factors — each maps to any object or custom field on the other side.
Change tracking / CDC tables System-maintained change records used to drive incremental sync. 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. Change tracking / CDC tables is specific to Azure SQL Database and Foundation Objects (FODepartment, FOLocation, FOCostCenter) to Success Factors — each maps to any object or custom field on the other side.
Tables The primary sync target; rows map one-to-one to records in the paired system. Position Position Management records for headcount and requisition planning; synced with an ATS or ERP to keep positions and reqs aligned. Tables is specific to Azure SQL Database and Position to Success Factors — each maps to any object or custom field on the other side.
Views Read-only projections used when the sync should expose a curated shape rather than raw tables. PerEmail and PerPhone Contact sub-entities under PerPerson; synced two-way with a directory or comms system to keep worker contact data current. Views is specific to Azure SQL Database and PerEmail and PerPhone to Success Factors — each maps to any object or custom field on the other side.
Schemas Namespaces that organize tables and control which objects a sync user can reach. 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. Schemas is specific to Azure SQL Database and User to Success Factors — each maps to any object or custom field on the other side.

How changes propagate between Azure SQL Database 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.

Azure SQL Database Success Factors Sub-second propagation

DetectionChanges in Azure SQL Database are captured at the source via change data capture — no polling loop against its API. Change data capture or change tracking, both supported on Azure SQL Database.

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

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

Rate-limit considerations

  • 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 Azure SQL Database ⇄ Success Factors

Connect Azure SQL Database and Success Factors for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure SQL Database 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 Azure SQL Database or Success Factors record.

Observability

Monitoring

Track your Azure SQL Database ⇄ 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 Azure SQL Database and Success Factors.

How the Azure SQL Database and Success Factors connectors work

Azure SQL Database

Integration surface
SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
Authentication
SQL authentication (database credentials) or Microsoft Entra ID authentication
Change detection
Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
Capabilities
read · write · CDC

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 Azure SQL Database 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 Azure SQL Database 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
    Azure SQL Database connected
    Success Factors connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure SQL Database 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 · Azure SQL Database ⇄ 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
    Azure SQL Database Success Factors
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure SQL Database 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.

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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 443 integrations available for Azure SQL Database and Success Factors.

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