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Human resources ⇄ Database

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

Keep Greenhouse and MarkLogic 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 MarkLogic

Put your workforce data where your apps can reach it: MarkLogic 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. MarkLogic 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 Documents, Collections, Semantic Triples, TDE Views in MarkLogic 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 Documents, Collections, Semantic Triples, TDE Views in MarkLogic 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 Keep reference datasets and semantically linked entities aligned across downstream applications.
  • 02 Feed harmonized entities into search and analytics applications as documents change.
  • 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

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.

Reporting and analytics on current data

Candidates, Applications, Jobs, Offers replicate into MarkLogic where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.

Org and structure stay aligned

Groups, departments, managers, and reporting lines from Greenhouse stay consistent in MarkLogic, so hierarchy-driven logic and permissions don't drift.

What you can sync between Greenhouse and MarkLogic

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 MarkLogic objects How this pairing syncs
Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Documents JSON and XML documents, the primary records read from and written to the database. Scorecards is specific to Greenhouse and Documents to MarkLogic — 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. Collections Named groupings used to scope which documents a sync reads or updates. Scheduled Interviews is specific to Greenhouse and Collections to MarkLogic — 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. Semantic Triples RDF data stored alongside documents, queryable with SPARQL for linked-data syncs. Users is specific to Greenhouse and Semantic Triples to MarkLogic — 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. TDE Views Relational projections of documents that let syncs read document data as SQL rows. Departments and Offices is specific to Greenhouse and TDE Views to MarkLogic — 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. Document Metadata & Properties Permissions, quality, and property fragments carried with each document. Candidates is specific to Greenhouse and Document Metadata & Properties to MarkLogic — 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. Databases & Forests Storage units that define the scope and placement of synced content. Applications is specific to Greenhouse and Databases & Forests to MarkLogic — each maps to any object or custom field on the other side.

How changes propagate between Greenhouse and MarkLogic

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

MarkLogic Greenhouse Interval-based propagation

DetectionStacksync polls MarkLogic for changes on an incremental schedule, reading only records changed since the previous pass. No exposed transaction log.

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 ⇄ MarkLogic

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenhouse or MarkLogic 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 MarkLogic record.

Observability

Monitoring

Track your Greenhouse ⇄ MarkLogic 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 MarkLogic.

How the Greenhouse and MarkLogic 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

MarkLogic

Integration surface
REST API (Client API), plus SQL/ODBC access over TDE views and Java/Node client libraries
Authentication
Username/password (digest or basic), with certificate-based options
Change detection
No exposed transaction log; polling on document timestamps/metadata, or server-side triggers that record changes for pickup
Capabilities
read · write
How it works

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

    Choose tables

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

Greenhouse and MarkLogic 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 438 integrations available for Greenhouse and MarkLogic.

Popular · 7 of 438
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