Skip to content
Database ⇄ Human resources

Azure SQL Database to Greenhouse integration — real-time, two-way sync

Keep Azure SQL Database 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 Azure SQL Database and Greenhouse

Put your workforce data where your apps can reach it: Azure SQL Database 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. Azure SQL Database is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Scheduled Interviews, Users, Departments and Offices, Candidates in Greenhouse need to exist as queryable Change tracking / CDC tables, Tables, Views, Schemas in Azure SQL Database 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 Change tracking / CDC tables, Tables, Views, Schemas in Azure SQL Database with Scheduled Interviews, Users, Departments and Offices, Candidates 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 Replicate Azure SQL tables to a warehouse without building custom CDC pipelines.
  • 02 Consolidate data from several line-of-business apps into one Azure SQL database as an integration hub.
  • 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

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

Scheduled Interviews, Users, Departments and Offices, Candidates replicate into Azure SQL Database 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 Azure SQL Database, so hierarchy-driven logic and permissions don't drift.

What you can sync between Azure SQL Database 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.

Azure SQL Database objects Greenhouse objects How this pairing syncs
Change tracking / CDC tables System-maintained change records used to drive incremental sync. Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. Change tracking / CDC tables is specific to Azure SQL Database and Departments and Offices to Greenhouse — each maps to any object or custom field on the other side.
Tables The primary sync target; rows map one-to-one to records in the paired system. Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. Tables is specific to Azure SQL Database and Candidates to Greenhouse — each maps to any object or custom field on the other side.
Views Read-only projections used when the sync should expose a curated shape rather than raw tables. Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Views is specific to Azure SQL Database and Applications to Greenhouse — each maps to any object or custom field on the other side.
Schemas Namespaces that organize tables and control which objects a sync user can reach. Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. Schemas is specific to Azure SQL Database and Jobs to Greenhouse — each maps to any object or custom field on the other side.
Rows and columns Standard relational records with typed columns; primary keys anchor upserts. Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Rows and columns is specific to Azure SQL Database and Offers to Greenhouse — each maps to any object or custom field on the other side.
Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Stored procedures is specific to Azure SQL Database and Scorecards to Greenhouse — each maps to any object or custom field on the other side.

How changes propagate between Azure SQL Database 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.

Azure SQL Database Greenhouse Sub-second propagation

DetectionChanges in Azure SQL Database are captured at the source via change data capture — no polling loop against its API. Change data capture or change tracking, both supported on Azure SQL Database.

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

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

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 Azure SQL Database ⇄ Greenhouse

Connect Azure SQL Database and Greenhouse for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure SQL Database 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 Azure SQL Database or Greenhouse record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Azure SQL Database and Greenhouse.

How the Azure SQL Database and Greenhouse connectors work

Azure SQL Database

Integration surface
SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
Authentication
SQL authentication (database credentials) or Microsoft Entra ID authentication
Change detection
Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
Capabilities
read · write · CDC

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 Azure SQL Database 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 Azure SQL Database 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
    Azure SQL Database connected
    Greenhouse connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Azure SQL Database 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 443 integrations available for Azure SQL Database and Greenhouse.

Popular · 7 of 443
All Azure SQL Database 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