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Human resources ⇄ Database

Greenhouse to Neo4j integration — real-time, two-way sync

Keep Greenhouse and Neo4j 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 Greenhouse and Neo4j

Put your workforce data where your apps can reach it: Neo4j and Greenhouse share the same people, positions, and org structure in real time.

Greenhouse is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. Neo4j is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Candidates, Applications, Jobs, Offers in Greenhouse need to exist as queryable Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j 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 Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j with Candidates, Applications, Jobs, Offers in Greenhouse field by field, in real time. You decide which system owns which fields — Greenhouse 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 Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
  • 02 Sync product catalog and order history into Neo4j to power recommendation queries.
  • 03 Write enriched or sourced Candidates from external tools into Greenhouse and keep contact fields refreshed as data changes.
  • 04 Stream Jobs, Departments, and Offices into a reporting database for recruiting funnel and time-to-fill dashboards.

Common sync patterns

Computed and operational fields flow back

Values assembled or corrected in Neo4j write onto the matching record in Greenhouse where those fields are writable, keeping the people system enriched.

Mirror people records into the database

Records maintained in Greenhouse land as queryable Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j, so internal apps and dashboards read live data instead of a periodic export.

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.

What you can sync between Greenhouse and Neo4j

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 Neo4j objects How this pairing syncs
Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Scorecards is specific to Greenhouse and Indexes & Constraints to Neo4j — 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. Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Scheduled Interviews is specific to Greenhouse and Databases to Neo4j — 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. Users & Roles Security principals controlling what an integration credential can query or modify. Users is specific to Greenhouse and Users & Roles to Neo4j — 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. Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Departments and Offices is specific to Greenhouse and Nodes to Neo4j — 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. Relationships Typed, directed edges that carry the connections syncs exist to model. Candidates is specific to Greenhouse and Relationships to Neo4j — 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. Properties Key-value attributes on both nodes and relationships, mapped from source fields. Applications is specific to Greenhouse and Properties to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between Greenhouse and Neo4j

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 Neo4j 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 written to Neo4j through its API, with automatic retries and rate-limit backoff.

Neo4j Greenhouse Sub-second propagation

DetectionChanges in Neo4j are captured at the source via change data capture — no polling loop against its API. Neo4j Change Data Capture on Enterprise and Aura streams graph changes.

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 ⇄ Neo4j

Connect Greenhouse and Neo4j for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Greenhouse–Neo4j connection.

Real-time

Two-way sync

Changes in Greenhouse or Neo4j instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenhouse or Neo4j 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 Neo4j record.

Observability

Monitoring

Track your Greenhouse ⇄ Neo4j 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 Neo4j.

How the Greenhouse and Neo4j 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

Neo4j

Integration surface
Bolt binary protocol with Cypher via official drivers, plus an HTTP query API
Authentication
Username/password (basic auth); enterprise deployments add SSO options
Change detection
Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties
Capabilities
read · write · CDC
How it works

How to connect Greenhouse to Neo4j — 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 Neo4j 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
    Neo4j connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Greenhouse and Neo4j 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 ⇄ Neo4j
    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 Neo4j
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Greenhouse and Neo4j 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 517 integrations available for Greenhouse and Neo4j.

Popular · 8 of 517
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