Skip to content
Data warehouse ⇄ Human resources

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

Keep Snowflake 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 Snowflake and Success Factors

Land the people and organization records from Success Factors in Snowflake as live tables for workforce reporting, without extract jobs, and write computed results back where Success Factors can use them.

Workforce data is some of the most requested data in the warehouse and some of the most awkward to move: the record types are many, the fields carry sensitive personal information, the APIs are strict, and hand-built extract jobs go stale or break quietly. Whether Success Factors is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in Snowflake next to everything else the company measures.

Stacksync syncs Position, PerEmail and PerPhone, User, PerPerson from Success Factors into tables in Snowflake continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Snowflake, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Success Factors where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.

Common use cases

  • 01 Activate modeled Snowflake tables by syncing scores and attributes back into CRM fields sales can act on
  • 02 Keep a customer 360 table aligned with its source systems in both directions instead of one-way reverse ETL
  • 03 Keep Foundation Objects (department, location, cost center) aligned between SuccessFactors and an ERP so cost-center and org hierarchies match.
  • 04 Write updated PerEmail, PerPhone, and User attributes back into SuccessFactors from an identity or directory system so contact data stays current.

Common sync patterns

Queryable history for planning and audit

A continuously synced copy in Snowflake gives you a durable, queryable record of how Success Factors's records change over time, for headcount planning and audit questions.

Write-back of computed values

Segments, rollups, or risk flags computed in Snowflake sync back onto the matching records in Success Factors, where the HR team sees them in the system they already use.

HR data in the warehouse, minus the pipeline

People and organization records from Success Factors arrive in Snowflake as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.

What you can sync between Snowflake 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.

Snowflake objects Success Factors objects How this pairing syncs
Schemas Namespaces within a database used to organize synced tables. EmpJob Effective-dated job info: position, department, manager, FTE, pay grade, cost center; the most-synced record for downstream HR and provisioning. Schemas is specific to Snowflake and EmpJob to Success Factors — each maps to any object or custom field on the other side.
Tables The main landing and activation target for synced records. EmpCompensation Effective-dated pay and compensation; usually read into a warehouse for reporting, writable for comp updates as new dated slices. Tables is specific to Snowflake and EmpCompensation to Success Factors — each maps to any object or custom field on the other side.
Views Modeled projections used as the source side of outbound syncs. 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. Views is specific to Snowflake and Foundation Objects (FODepartment, FOLocation, FOCostCenter) to Success Factors — each maps to any object or custom field on the other side.
Materialized Views Precomputed results synced outward for low-latency reads. Position Position Management records for headcount and requisition planning; synced with an ATS or ERP to keep positions and reqs aligned. Materialized Views is specific to Snowflake and Position to Success Factors — each maps to any object or custom field on the other side.
Streams Row-level change records on a table, consumed to process deltas instead of full scans. PerEmail and PerPhone Contact sub-entities under PerPerson; synced two-way with a directory or comms system to keep worker contact data current. Streams is specific to Snowflake and PerEmail and PerPhone to Success Factors — each maps to any object or custom field on the other side.
Stages File staging areas used for bulk loads into synced tables. 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. Stages is specific to Snowflake and User to Success Factors — each maps to any object or custom field on the other side.

How changes propagate between Snowflake 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.

Snowflake Success Factors Sub-second propagation

DetectionChanges in Snowflake are captured at the source via change data capture — no polling loop against its API. The setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism.

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

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

Rate-limit considerations

  • Snowflake: No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time.
  • 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 Snowflake ⇄ Success Factors

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Snowflake 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 Snowflake or Success Factors record.

Observability

Monitoring

Track your Snowflake ⇄ 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 Snowflake and Success Factors.

How the Snowflake and Success Factors connectors work

Snowflake

Integration surface
SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
Authentication
Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
Change detection
Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
Capabilities
read · write · CDC
Rate limits
No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
Snowflake setup guide

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

    Choose tables

    Pick the Snowflake 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 · Snowflake ⇄ 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
    Snowflake Success Factors
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Snowflake 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 547 integrations available for Snowflake and Success Factors.

Popular · 8 of 547
All Snowflake 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