Skip to content
Database ⇄ Human resources

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

Keep DuckDB 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.

  • 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 DuckDB and Greenhouse

Put your workforce data where your apps can reach it: DuckDB 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. DuckDB is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Users, Departments and Offices, Candidates, Applications in Greenhouse need to exist as queryable External files (Parquet/CSV/JSON), Attached databases, Database files, Schemas in DuckDB 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 External files (Parquet/CSV/JSON), Attached databases, Database files, Schemas in DuckDB with Users, Departments and Offices, Candidates, Applications 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 Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
  • 02 Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
  • 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

Org and structure stay aligned

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

Computed and operational fields flow back

Values assembled or corrected in DuckDB 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 External files (Parquet/CSV/JSON), Attached databases, Database files, Schemas in DuckDB, so internal apps and dashboards read live data instead of a periodic export.

What you can sync between DuckDB 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.

DuckDB objects Greenhouse objects How this pairing syncs
Schemas Namespaces within a database used to organize tables in sync outputs. Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Schemas is specific to DuckDB and Scorecards to Greenhouse — each maps to any object or custom field on the other side.
Tables Columnar tables created via SQL; the destination for materialized sync data. Scheduled Interviews Interview events with interviewers, times, and rooms; full create/update/delete support for calendar and reporting syncs. Tables is specific to DuckDB and Scheduled Interviews to Greenhouse — each maps to any object or custom field on the other side.
Views SQL views used to shape or filter data for downstream consumers. Users Greenhouse users (recruiters, hiring managers); read and written, and referenced by the On-Behalf-Of header on every write. Views is specific to DuckDB and Users to Greenhouse — each maps to any object or custom field on the other side.
External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. External files (Parquet/CSV/JSON) is specific to DuckDB and Departments and Offices to Greenhouse — each maps to any object or custom field on the other side.
Attached databases Additional database files or external systems attached into one session for cross-source queries. Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. Attached databases is specific to DuckDB and Candidates to Greenhouse — each maps to any object or custom field on the other side.
Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Database files is specific to DuckDB and Applications to Greenhouse — each maps to any object or custom field on the other side.

How changes propagate between DuckDB 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.

DuckDB Greenhouse Interval-based propagation

DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.

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

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

Rate-limit considerations

  • DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
  • 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 DuckDB ⇄ Greenhouse

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DuckDB 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 DuckDB or Greenhouse record.

Observability

Monitoring

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

Trading partners

EDI

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

How the DuckDB and Greenhouse connectors work

DuckDB

Integration surface
In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
Authentication
None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
Change detection
Polling or full re-reads; no change feed or transaction log API
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by local compute and I/O

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 DuckDB 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 DuckDB 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
    DuckDB connected
    Greenhouse connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

DuckDB and Greenhouse 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 448 integrations available for DuckDB and Greenhouse.

Popular · 8 of 448
All DuckDB integrations All Greenhouse 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