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Human resources ⇄ Database

Greenhouse to Redis Enterprise integration — real-time, two-way sync

Keep Greenhouse and Redis Enterprise 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 Greenhouse and Redis Enterprise

Put your workforce data where your apps can reach it: Redis Enterprise 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. Redis Enterprise is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Applications, Jobs, Offers, Scorecards in Greenhouse need to exist as queryable Keys (Strings), Hashes, JSON documents, Sets in Redis Enterprise 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 Keys (Strings), Hashes, JSON documents, Sets in Redis Enterprise with Applications, Jobs, Offers, Scorecards 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 Sync Postgres reference tables into RedisJSON documents that power API responses and personalization lookups.
  • 02 Publish record-change events into Redis Streams so microservices react to upstream CRM updates without polling.
  • 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

Mirror people records into the database

Records maintained in Greenhouse land as queryable Keys (Strings), Hashes, JSON documents, Sets in Redis Enterprise, so internal apps and dashboards read live data instead of a periodic export.

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

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

What you can sync between Greenhouse and Redis Enterprise

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 Redis Enterprise objects How this pairing syncs
Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. Streams Append-only logs with consumer groups, used to fan sync events out to downstream services. Candidates is specific to Greenhouse and Streams to Redis Enterprise — 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. Pub/Sub channels Fire-and-forget messaging used to notify applications when synced keys change. Applications is specific to Greenhouse and Pub/Sub channels to Redis Enterprise — each maps to any object or custom field on the other side.
Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. Search indexes Secondary indexes (RediSearch) that make synced hashes and JSON documents queryable. Jobs is specific to Greenhouse and Search indexes to Redis Enterprise — each maps to any object or custom field on the other side.
Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Keys (Strings) Simple key-value pairs used to cache individual synced records or lookup values. Offers is specific to Greenhouse and Keys (Strings) to Redis Enterprise — each maps to any object or custom field on the other side.
Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Hashes Field-value maps that commonly hold one synced row per hash, keyed by record ID. Scorecards is specific to Greenhouse and Hashes to Redis Enterprise — 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. JSON documents Native JSON storage (RedisJSON) for nested records synced from APIs or document stores. Scheduled Interviews is specific to Greenhouse and JSON documents to Redis Enterprise — each maps to any object or custom field on the other side.

How changes propagate between Greenhouse and Redis Enterprise

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

Redis Enterprise Greenhouse Interval-based propagation

DetectionStacksync polls Redis Enterprise for changes on an incremental schedule, reading only records changed since the previous pass. Keyspace notifications over pub/sub or reads from Redis Streams.

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.
  • Redis Enterprise: Throughput is bounded by provisioned cluster capacity rather than published API rate limits.
What ships with Greenhouse ⇄ Redis Enterprise

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenhouse or Redis Enterprise 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 Redis Enterprise record.

Observability

Monitoring

Track your Greenhouse ⇄ Redis Enterprise 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 Redis Enterprise.

How the Greenhouse and Redis Enterprise 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

Redis Enterprise

Integration surface
Redis wire protocol (RESP) via client libraries; separate REST API for cluster management
Authentication
Password or ACL-based credentials, typically over TLS
Change detection
Keyspace notifications over pub/sub or reads from Redis Streams; no transaction-log CDC surface for data
Capabilities
read · write
Rate limits
Throughput is bounded by provisioned cluster capacity rather than published API rate limits
How it works

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

    Choose tables

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

Greenhouse and Redis Enterprise 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 434 integrations available for Greenhouse and Redis Enterprise.

Popular · 8 of 434
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