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Database ⇄ Human resources

Amazon RDS to Greenhouse integration — real-time, two-way sync

Keep Amazon RDS 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.

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Why teams connect Amazon RDS and Greenhouse

Put your workforce data where your apps can reach it: Amazon RDS 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. Amazon RDS 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 Views, Columns, Primary and Unique Keys, Read Replicas in Amazon RDS 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 Views, Columns, Primary and Unique Keys, Read Replicas in Amazon RDS 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 Use a read replica as the sync source to keep change capture load off the primary instance
  • 02 Bi-directional sync between an RDS database and a CRM so application data and sales data stay consistent without custom integration code
  • 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 Amazon RDS 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 Amazon RDS, so hierarchy-driven logic and permissions don't drift.

What you can sync between Amazon RDS 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.

Amazon RDS objects Greenhouse objects How this pairing syncs
Read Replicas Low-impact read endpoints often used as the source side of a sync. Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Read Replicas is specific to Amazon RDS and Offers to Greenhouse — each maps to any object or custom field on the other side.
Stored Procedures Engine-specific logic that can react to synced rows. Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Stored Procedures is specific to Amazon RDS and Scorecards to Greenhouse — each maps to any object or custom field on the other side.
Databases Engine-level databases on the instance that scope a sync's reads and writes. Scheduled Interviews Interview events with interviewers, times, and rooms; full create/update/delete support for calendar and reporting syncs. Databases is specific to Amazon RDS and Scheduled Interviews to Greenhouse — each maps to any object or custom field on the other side.
Schemas Namespaces within a database used to isolate synced tables. Users Greenhouse users (recruiters, hiring managers); read and written, and referenced by the On-Behalf-Of header on every write. Schemas is specific to Amazon RDS and Users to Greenhouse — each maps to any object or custom field on the other side.
Tables The core sync target; rows map to records in connected SaaS systems. Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. Tables is specific to Amazon RDS and Departments and Offices to Greenhouse — each maps to any object or custom field on the other side.
Views Read-side projections exposed to outbound syncs. Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. Views is specific to Amazon RDS and Candidates to Greenhouse — each maps to any object or custom field on the other side.

How changes propagate between Amazon RDS 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.

Amazon RDS Greenhouse Sub-second propagation

DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.

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

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

Rate-limit considerations

  • Amazon RDS: No API rate limits; throughput depends on instance class, storage IOPS, and connection limits.
  • 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 Amazon RDS ⇄ Greenhouse

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon RDS 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 Amazon RDS or Greenhouse record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Amazon RDS and Greenhouse connectors work

Amazon RDS

Integration surface
SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle)
Authentication
Database credentials over SSL/TLS, or IAM database authentication on supported engines
Change detection
Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC; enabled through RDS parameter groups, with polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance class, storage IOPS, and connection limits

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

    Choose tables

    Pick the Amazon RDS 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 · Amazon RDS ⇄ 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
    Amazon RDS Greenhouse
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon RDS 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.

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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 454 integrations available for Amazon RDS and Greenhouse.

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