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Data warehouse ⇄ Human resources

Amazon Redshift to Greenhouse integration — real-time, two-way sync

Keep Amazon Redshift and Greenhouse 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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Why teams connect Amazon Redshift and Greenhouse

Land the people and organization records from Greenhouse in Amazon Redshift 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 Amazon Redshift next to everything else the company measures.

Stacksync syncs Jobs, Offers, Scorecards, Scheduled Interviews from Greenhouse into tables in Amazon Redshift continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Amazon Redshift, 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 Feed customer 360 tables built in Redshift to support and success platforms.
  • 02 Centralize CRM, ERP, and product data in Redshift so analysts join it with warehouse tables.
  • 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

HR data in the warehouse, minus the pipeline

People and organization records from Greenhouse arrive in Amazon Redshift 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 Amazon Redshift 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.

What you can sync between Amazon Redshift and Greenhouse

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.

Amazon Redshift objects Greenhouse objects How this pairing syncs
Tables Columnar tables used as sync destinations for SaaS and database data. Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Tables is specific to Amazon Redshift and Applications to Greenhouse — each maps to any object or custom field on the other side.
Views SQL views readable as modeled sources for reverse syncs. Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. Views is specific to Amazon Redshift and Jobs to Greenhouse — each maps to any object or custom field on the other side.
Materialized Views Precomputed results that downstream syncs can read for performance. Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Materialized Views is specific to Amazon Redshift and Offers to Greenhouse — each maps to any object or custom field on the other side.
External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. External Tables (Spectrum) is specific to Amazon Redshift and Scorecards to Greenhouse — each maps to any object or custom field on the other side.
Stored Procedures SQL procedures sometimes invoked around load steps. Scheduled Interviews Interview events with interviewers, times, and rooms; full create/update/delete support for calendar and reporting syncs. Stored Procedures is specific to Amazon Redshift and Scheduled Interviews to Greenhouse — each maps to any object or custom field on the other side.
Users and Groups Principals used to grant a sync connection scoped access. Users Greenhouse users (recruiters, hiring managers); read and written, and referenced by the On-Behalf-Of header on every write. Users and Groups is specific to Amazon Redshift and Users to Greenhouse — each maps to any object or custom field on the other side.

How changes propagate between Amazon Redshift and Greenhouse

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.

Amazon Redshift Greenhouse Interval-based propagation

DetectionStacksync polls Amazon Redshift for changes on an incremental schedule, reading only records changed since the previous pass. Polling or query-based diffing.

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

Greenhouse Amazon Redshift 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 Amazon Redshift as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon Redshift: Bounded by cluster or serverless capacity and concurrency settings rather than API quotas.
  • 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.
What ships with Amazon Redshift ⇄ Greenhouse

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Redshift or Greenhouse 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 Amazon Redshift or Greenhouse record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Amazon Redshift and Greenhouse connectors work

Amazon Redshift

Integration surface
SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS
Authentication
Database credentials or IAM-based authentication
Change detection
Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers
Capabilities
read · write
Rate limits
Bounded by cluster or serverless capacity and concurrency settings rather than API quotas

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
How it works

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

    Choose tables

    Pick the Amazon Redshift and Greenhouse 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 · Amazon Redshift ⇄ Greenhouse
    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
    Amazon Redshift Greenhouse
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Redshift and Greenhouse 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 542 integrations available for Amazon Redshift and Greenhouse.

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