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Data warehouse ⇄ Human resources

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

Keep Apache Impala 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 Apache Impala and Success Factors

Land the people and organization records from Success Factors in Apache Impala 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 Apache Impala next to everything else the company measures.

Stacksync syncs PerPerson, EmpEmployment, EmpJob, EmpCompensation from Success Factors into tables in Apache Impala continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Apache Impala, 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 Read new partitions incrementally from Parquet tables and land them in a cloud warehouse during migration.
  • 02 Publish Impala query results (aggregates, KPIs) to CRMs or spreadsheets on a schedule.
  • 03 Replicate EmpCompensation and EmpJob effective-dated history into a warehouse for headcount, attrition, and compensation reporting without CSV pulls.
  • 04 Keep Foundation Objects (department, location, cost center) aligned between SuccessFactors and an ERP so cost-center and org hierarchies match.

Common sync patterns

Headcount and cost joined with everything else

Analysts combine Success Factors's workforce records with finance, product, or operational data already in Apache Impala for reporting the HR system cannot produce on its own.

Fresh data instead of last night's load

Because changes stream continuously, reports query current workforce data rather than waiting for an overnight load window to finish.

Queryable history for planning and audit

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

What you can sync between Apache Impala 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.

Apache Impala objects Success Factors objects How this pairing syncs
Views Logical views readable as modeled sources. 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 Apache Impala and Foundation Objects (FODepartment, FOLocation, FOCostCenter) to Success Factors — each maps to any object or custom field on the other side.
Kudu Tables Kudu-backed tables that support row-level insert, update, upsert, and delete. Position Position Management records for headcount and requisition planning; synced with an ATS or ERP to keep positions and reqs aligned. Kudu Tables is specific to Apache Impala and Position to Success Factors — each maps to any object or custom field on the other side.
External Tables Tables over files loaded by other tools, queryable without data movement. PerEmail and PerPhone Contact sub-entities under PerPerson; synced two-way with a directory or comms system to keep worker contact data current. External Tables is specific to Apache Impala and PerEmail and PerPhone to Success Factors — each maps to any object or custom field on the other side.
Users and Roles Principals (often via Ranger/Sentry) used to grant scoped read access. 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. Users and Roles is specific to Apache Impala and User to Success Factors — each maps to any object or custom field on the other side.
Databases Namespaces shared with the Hive Metastore that scope tables. PerPerson Person-level container in Employee Central holding biographical data; effective-dated child entities (PerPersonal, PerEmail, PerPhone) hang off it. Databases is specific to Apache Impala and PerPerson to Success Factors — each maps to any object or custom field on the other side.
Tables HDFS or object-storage backed tables (commonly Parquet) read at interactive speed. EmpEmployment Employment record tying a person to an employment period (hire, service dates); carries lastModifiedDateTime used for incremental polling. Tables is specific to Apache Impala and EmpEmployment to Success Factors — each maps to any object or custom field on the other side.

How changes propagate between Apache Impala 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.

Apache Impala Success Factors Interval-based propagation

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

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

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

Rate-limit considerations

  • Apache Impala: No API quotas; concurrency is bounded by cluster resources and admission control settings.
  • 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 Apache Impala ⇄ Success Factors

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Impala 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 Apache Impala or Success Factors record.

Observability

Monitoring

Track your Apache Impala ⇄ 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 Apache Impala and Success Factors.

How the Apache Impala and Success Factors connectors work

Apache Impala

Integration surface
SQL over JDBC/ODBC (HiveServer2-compatible protocol)
Authentication
Deployment-dependent: Kerberos, LDAP, or username/password
Change detection
Polling on partition or timestamp columns; no change log exposed for external consumers
Capabilities
read · write
Rate limits
No API quotas; concurrency is bounded by cluster resources and admission control settings

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

    Choose tables

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

Apache Impala and Success Factors integration FAQ

SECURITY

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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 435 integrations available for Apache Impala and Success Factors.

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