Skip to content
Database ⇄ Human resources

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

Keep Elasticsearch 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 Elasticsearch and Greenhouse

Put your workforce data where your apps can reach it: Elasticsearch 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. Elasticsearch 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 Index templates, Indices, Documents, Index mappings in Elasticsearch 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 Index templates, Indices, Documents, Index mappings in Elasticsearch 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 Push product catalog data from an ERP or commerce database into Elasticsearch for storefront search.
  • 02 Mirror support tickets into an index used for full-text search and agent-assist tooling.
  • 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

Org and structure stay aligned

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

Computed and operational fields flow back

Values assembled or corrected in Elasticsearch 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 Index templates, Indices, Documents, Index mappings in Elasticsearch, so internal apps and dashboards read live data instead of a periodic export.

What you can sync between Elasticsearch 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.

Elasticsearch objects Greenhouse objects How this pairing syncs
Documents The unit of sync; JSON records created, updated, and deleted by _id. Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. Documents is specific to Elasticsearch and Departments and Offices to Greenhouse — each maps to any object or custom field on the other side.
Index mappings Field type definitions that determine how synced fields are indexed and queried. Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. Index mappings is specific to Elasticsearch and Candidates to Greenhouse — each maps to any object or custom field on the other side.
Aliases Stable read/write names that let a sync cut over between index versions without downtime. Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Aliases is specific to Elasticsearch and Applications to Greenhouse — each maps to any object or custom field on the other side.
Data streams Append-only targets for time-series or event data pushed from source systems. Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. Data streams is specific to Elasticsearch and Jobs to Greenhouse — each maps to any object or custom field on the other side.
Ingest pipelines Server-side transforms applied to documents as a sync writes them. Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Ingest pipelines is specific to Elasticsearch and Offers to Greenhouse — each maps to any object or custom field on the other side.
Index templates Reusable settings and mappings applied automatically to new indices a sync creates. Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Index templates is specific to Elasticsearch and Scorecards to Greenhouse — each maps to any object or custom field on the other side.

How changes propagate between Elasticsearch 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.

Elasticsearch Greenhouse Interval-based propagation

DetectionStacksync polls Elasticsearch for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or sequence fields.

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

Greenhouse Elasticsearch 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 Elasticsearch through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Elasticsearch: No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity.
  • 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 Elasticsearch ⇄ Greenhouse

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Elasticsearch 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 Elasticsearch or Greenhouse record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Elasticsearch and Greenhouse connectors work

Elasticsearch

Integration surface
REST API (JSON over HTTP)
Authentication
API keys or basic authentication; Elastic Cloud also issues service account tokens
Change detection
Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
Capabilities
read · write
Rate limits
No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity

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

    Choose tables

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

Elasticsearch 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 520 integrations available for Elasticsearch and Greenhouse.

Popular · 8 of 520
All Elasticsearch 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