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Human resources ⇄ Data warehouse

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

Keep Greenhouse and Materialize 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Greenhouse and Materialize

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

Stacksync syncs Departments and Offices, Candidates, Applications, Jobs from Greenhouse into tables in Materialize continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Materialize, 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 Read computed view results back into a CRM or application database as derived fields.
  • 02 Drive alerting and operational tooling from SUBSCRIBE change streams instead of scheduled queries.
  • 03 Export Scorecards and Scheduled Interviews to a data warehouse to analyze interviewer load and interview outcomes.
  • 04 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.

Common sync patterns

Queryable history for planning and audit

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

Write-back of computed values

Segments, rollups, or risk flags computed in Materialize 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 Materialize as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.

What you can sync between Greenhouse and Materialize

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 Materialize objects How this pairing syncs
Scheduled Interviews Interview events with interviewers, times, and rooms; full create/update/delete support for calendar and reporting syncs. Connections & Secrets Stored credentials and endpoints used by sources and sinks. Scheduled Interviews is specific to Greenhouse and Connections & Secrets to Materialize — 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. Schemas & Databases Namespaces that organize objects a sync targets. Users is specific to Greenhouse and Schemas & Databases to Materialize — each maps to any object or custom field on the other side.
Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. Departments and Offices is specific to Greenhouse and Tables to Materialize — each maps to any object or custom field on the other side.
Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. Candidates is specific to Greenhouse and Sources to Materialize — each maps to any object or custom field on the other side.
Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. Applications is specific to Greenhouse and Materialized Views to Materialize — 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. Sinks Outbound connections that emit view changes to Kafka topics. Jobs is specific to Greenhouse and Sinks to Materialize — each maps to any object or custom field on the other side.

How changes propagate between Greenhouse and Materialize

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 Materialize 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 Materialize as a row-level write, with types converted between the two schemas.

Materialize Greenhouse Sub-second propagation

DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.

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.
What ships with Greenhouse ⇄ Materialize

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenhouse or Materialize 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 Materialize record.

Observability

Monitoring

Track your Greenhouse ⇄ Materialize 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 Materialize.

How the Greenhouse and Materialize 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

Materialize

Integration surface
PostgreSQL wire protocol (SQL)
Authentication
Database credentials (username/password; app passwords in the managed cloud service)
Change detection
SUBSCRIBE queries stream row-level changes of any view or table to the client
Capabilities
read · write · CDC
How it works

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

    Choose tables

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

Greenhouse and Materialize 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.

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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 437 integrations available for Greenhouse and Materialize.

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