Skip to content
Human resources ⇄ Data warehouse

Greenhouse to StarRocks integration — real-time, two-way sync

Keep Greenhouse and StarRocks 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 Greenhouse and StarRocks

Land the people and organization records from Greenhouse in StarRocks as live tables for workforce reporting, without extract jobs, and write computed results back where Greenhouse 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 Greenhouse is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in StarRocks next to everything else the company measures.

Stacksync syncs Scorecards, Scheduled Interviews, Users, Departments and Offices from Greenhouse into tables in StarRocks continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in StarRocks, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Greenhouse 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 Continuously apply upserts from operational databases into Primary Key tables to keep analytics current
  • 02 Serve customer-facing analytics from SaaS data synced into one analytical store
  • 03 Two-way sync Candidates and Applications with Postgres so recruiting-ops apps read and update stage, status, and custom fields in SQL while recruiters stay in Greenhouse.
  • 04 Write enriched or sourced Candidates from external tools into Greenhouse and keep contact fields refreshed as data changes.

Common sync patterns

Write-back of computed values

Segments, rollups, or risk flags computed in StarRocks sync back onto the matching records in Greenhouse, 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 Greenhouse arrive in StarRocks as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.

Headcount and cost joined with everything else

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

What you can sync between Greenhouse and StarRocks

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.

Greenhouse objects StarRocks objects How this pairing syncs
Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Databases Top-level namespaces addressed exactly as in MySQL clients. Applications is specific to Greenhouse and Databases to StarRocks — each maps to any object or custom field on the other side.
Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. Tables Defined with a table model (Primary Key, Unique Key, Aggregate, Duplicate Key) that determines update behavior. Jobs is specific to Greenhouse and Tables to StarRocks — each maps to any object or custom field on the other side.
Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Materialized views Automatically maintained rollups used to accelerate queries on synced data. Offers is specific to Greenhouse and Materialized views to StarRocks — each maps to any object or custom field on the other side.
Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Views Logical views for shaping analytical reads. Scorecards is specific to Greenhouse and Views to StarRocks — each maps to any object or custom field on the other side.
Scheduled Interviews Interview events with interviewers, times, and rooms; full create/update/delete support for calendar and reporting syncs. Partitions Time or range partitions that scope loads and retention. Scheduled Interviews is specific to Greenhouse and Partitions to StarRocks — each maps to any object or custom field on the other side.
Users Greenhouse users (recruiters, hiring managers); read and written, and referenced by the On-Behalf-Of header on every write. Columns Columnar storage with types mapped from source systems during sync. Users is specific to Greenhouse and Columns to StarRocks — each maps to any object or custom field on the other side.

How changes propagate between Greenhouse and StarRocks

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.

Greenhouse StarRocks Sub-second propagation

DetectionGreenhouse notifies Stacksync of record changes through webhook events. HMAC-SHA256 signed webhooks for candidate, application, job, and interview events, plus polling list endpoints with created_after / updated_after /.

DeliveryEach detected change is applied to StarRocks as a row-level write, with types converted between the two schemas.

StarRocks Greenhouse Interval-based propagation

DetectionStacksync polls StarRocks for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling when reading.

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

Rate-limit considerations

  • Greenhouse: Harvest enforces a per-integration limit over a rolling 10-second window (X-RateLimit-Limit, commonly 50 requests / 10s for approved integrations); responses carry X-RateLimit-Remaining and, on a 429, X-RateLimit-Reset and Retry-After.
  • StarRocks: Ingestion throughput is bounded by cluster resources rather than API quotas.
What ships with Greenhouse ⇄ StarRocks

Connect Greenhouse and StarRocks for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Greenhouse–StarRocks connection.

Real-time

Two-way sync

Changes in Greenhouse or StarRocks instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenhouse or StarRocks 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 Greenhouse or StarRocks record.

Observability

Monitoring

Track your Greenhouse ⇄ StarRocks sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Greenhouse and StarRocks.

How the Greenhouse and StarRocks connectors work

Greenhouse

Integration surface
Harvest REST API (plus read-only Job Board API and the Ingestion API for bulk candidate import)
Authentication
HTTP Basic Auth with a Harvest API key (key as username, blank password, colon appended then Base64-encoded); write calls require an On-Behalf-Of header naming the Greenhouse user
Change detection
HMAC-SHA256 signed webhooks for candidate, application, job, and interview events, plus polling list endpoints with created_after / updated_after / last_activity_after filters
Capabilities
read · write · webhooks
Rate limits
Harvest enforces a per-integration limit over a rolling 10-second window (X-RateLimit-Limit, commonly 50 requests / 10s for approved integrations); responses carry X-RateLimit-Remaining and, on a 429, X-RateLimit-Reset and Retry-After.
Greenhouse setup guide

StarRocks

Integration surface
MySQL wire protocol for SQL; HTTP-based Stream Load API for ingestion
Authentication
Database credentials (MySQL-compatible username/password)
Change detection
Query-based polling when reading; StarRocks is most often the destination side of a sync
Capabilities
read · write
Rate limits
Ingestion throughput is bounded by cluster resources rather than API quotas
How it works

How to connect Greenhouse to StarRocks — 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 Greenhouse and StarRocks 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
    Greenhouse connected
    StarRocks connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Greenhouse and StarRocks 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 · Greenhouse ⇄ StarRocks
    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
    Greenhouse StarRocks
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Greenhouse and StarRocks 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 434 integrations available for Greenhouse and StarRocks.

Popular · 7 of 434
All Greenhouse integrations All StarRocks 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