Two-way sync
Changes in Greenhouse or IBM Netezza instantly reflect in both systems. No stale data, no manual imports.
Keep Greenhouse and IBM Netezza in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Workforce data is some of the most requested data in the warehouse and some of the most awkward to move: the record types are many, the fields carry sensitive personal information, the APIs are strict, and hand-built extract jobs go stale or break quietly. Whether Greenhouse is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in IBM Netezza next to everything else the company measures.
Stacksync syncs Applications, Jobs, Offers, Scorecards from Greenhouse into tables in IBM Netezza continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in IBM Netezza, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Greenhouse where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.
People and organization records from Greenhouse arrive in IBM Netezza as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.
Analysts combine Greenhouse's workforce records with finance, product, or operational data already in IBM Netezza for reporting the HR system cannot produce on its own.
Because changes stream continuously, reports query current workforce data rather than waiting for an overnight load window to finish.
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 | IBM Netezza objects | How this pairing syncs | |
|---|---|---|---|
| Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. | Sequences Key generators referenced when writing new rows. | Jobs is specific to Greenhouse and Sequences to IBM Netezza — 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. | External tables File-backed load/unload paths used for bulk movement alongside row-level syncs. | Offers is specific to Greenhouse and External tables to IBM Netezza — 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. | Databases Top-level containers that scope a sync connection. | Scorecards is specific to Greenhouse and Databases to IBM Netezza — 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. | Schemas Namespace tables within a database. | Scheduled Interviews is specific to Greenhouse and Schemas to IBM Netezza — each maps to any object or custom field on the other side. | |
| Users Greenhouse users (recruiters, hiring managers); read and written, and referenced by the On-Behalf-Of header on every write. | Tables Distributed tables mapped directly to sync targets. | Users is specific to Greenhouse and Tables to IBM Netezza — each maps to any object or custom field on the other side. | |
| Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. | Views Read-only projections used to shape outbound data. | Departments and Offices is specific to Greenhouse and Views to IBM Netezza — each maps to any object or custom field on the other side. |
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.
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 IBM Netezza as a row-level write, with types converted between the two schemas.
DetectionStacksync polls IBM Netezza for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key-based cursors.
DeliveryEach detected change is written to Greenhouse through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Greenhouse–IBM Netezza connection.
Changes in Greenhouse or IBM Netezza instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Greenhouse or IBM Netezza data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Greenhouse or IBM Netezza record.
Track your Greenhouse ⇄ IBM Netezza sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Greenhouse and IBM Netezza.
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.
Authenticate Greenhouse and IBM Netezza with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Greenhouse and IBM Netezza 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Greenhouse and IBM Netezza: authenticate both systems, choose the objects to sync (such as Greenhouse's Jobs and Offers), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Greenhouse: HMAC-SHA256 signed webhooks for candidate, application, job, and interview events, plus polling list endpoints with created_after / updated_after / last_activity_after filters. On IBM Netezza: Polling with timestamp or key-based cursors; no log-based CDC is exposed. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the IBM Netezza side: Materialized views, Sequences, External tables, Databases, plus custom fields where IBM Netezza exposes them. On the Greenhouse side: Applications, Jobs, Offers, Scorecards. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Greenhouse and IBM Netezza: HR data in the warehouse, minus the pipeline; Headcount and cost joined with everything else; Fresh data instead of last night's load. People and organization records from Greenhouse arrive in IBM Netezza as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.
Greenhouse: 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. IBM Netezza: SQL over JDBC/ODBC (Netezza's SQL dialect derives from PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
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Every pair below is a real-time, two-way sync. Search all 439 integrations available for Greenhouse and IBM Netezza.