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Database ⇄ Human resources

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

Keep SingleStore 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

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Why teams connect SingleStore and Success Factors

Put your workforce data where your apps can reach it: SingleStore 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. SingleStore 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 Tables (rowstore and columnstore), Views, Reference Tables, Pipelines in SingleStore 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 Tables (rowstore and columnstore), Views, Reference Tables, Pipelines in SingleStore 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 Consolidate data from transactional databases and SaaS apps into one store that handles both lookups and scans.
  • 02 Keep reference data consistent between SingleStore and application databases.
  • 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

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.

Reporting and analytics on current data

PerEmail and PerPhone, User, PerPerson, EmpEmployment replicate into SingleStore 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 SingleStore, so hierarchy-driven logic and permissions don't drift.

What you can sync between SingleStore 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.

SingleStore objects Success Factors objects How this pairing syncs
Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. EmpEmployment Employment record tying a person to an employment period (hire, service dates); carries lastModifiedDateTime used for incremental polling. Tables (rowstore and columnstore) is specific to SingleStore and EmpEmployment to Success Factors — each maps to any object or custom field on the other side.
Views Read-only projections used as curated sync sources. EmpJob Effective-dated job info: position, department, manager, FTE, pay grade, cost center; the most-synced record for downstream HR and provisioning. Views is specific to SingleStore and EmpJob to Success Factors — each maps to any object or custom field on the other side.
Reference Tables Small tables replicated to every node, often used for dimension data in syncs. EmpCompensation Effective-dated pay and compensation; usually read into a warehouse for reporting, writable for comp updates as new dated slices. Reference Tables is specific to SingleStore and EmpCompensation to Success Factors — each maps to any object or custom field on the other side.
Pipelines Native ingestion jobs from Kafka or object storage that coexist with external 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. Pipelines is specific to SingleStore and Foundation Objects (FODepartment, FOLocation, FOCostCenter) to Success Factors — each maps to any object or custom field on the other side.
Stored Procedures Existing logic sometimes invoked on write paths. Position Position Management records for headcount and requisition planning; synced with an ATS or ERP to keep positions and reqs aligned. Stored Procedures is specific to SingleStore and Position to Success Factors — each maps to any object or custom field on the other side.
Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys. PerEmail and PerPhone Contact sub-entities under PerPerson; synced two-way with a directory or comms system to keep worker contact data current. Indexes and Shard Keys is specific to SingleStore and PerEmail and PerPhone to Success Factors — each maps to any object or custom field on the other side.

How changes propagate between SingleStore 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.

SingleStore Success Factors Interval-based propagation

DetectionStacksync polls SingleStore for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or watermark columns.

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

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

Rate-limit considerations

  • SingleStore: No API rate limits; throughput is bounded by workspace or cluster size.
  • 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 SingleStore ⇄ Success Factors

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever SingleStore 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 SingleStore or Success Factors record.

Observability

Monitoring

Track your SingleStore ⇄ 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 SingleStore and Success Factors.

How the SingleStore and Success Factors connectors work

SingleStore

Integration surface
SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
Authentication
Database credentials
Change detection
Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by workspace or cluster size

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

    Choose tables

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

SingleStore 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 449 integrations available for SingleStore and Success Factors.

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