Real-time
Two-way sync
Changes in Dynamo DB or Greenhouse instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Human resources
Dynamo DB to Greenhouse integration — real-time, two-way sync
Keep Dynamo DB 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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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Dynamo DB and Greenhouse
Put your workforce data where your apps can reach it: Dynamo DB 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. Dynamo DB is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Scorecards, Scheduled Interviews, Users, Departments and Offices in Greenhouse need to exist as queryable Global Tables, Tables, Items, Attributes in Dynamo DB 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 Global Tables, Tables, Items, Attributes in Dynamo DB with Scorecards, Scheduled Interviews, Users, Departments and Offices 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 Mirror SaaS objects into DynamoDB items to serve low-latency lookups from production services.
- 02 Consolidate multi-region Global Tables data into a single reporting store.
- 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
Reporting and analytics on current data
Scorecards, Scheduled Interviews, Users, Departments and Offices replicate into Dynamo DB 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 Dynamo DB, so hierarchy-driven logic and permissions don't drift.
Computed and operational fields flow back
Values assembled or corrected in Dynamo DB write onto the matching record in Greenhouse where those fields are writable, keeping the people system enriched.
What you can sync between Dynamo DB 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.
| Dynamo DB objects | Greenhouse objects | How this pairing syncs | |
|---|---|---|---|
| Items Schemaless records keyed by partition (and optional sort) key, mapped to rows or SaaS objects in syncs. | Departments and Offices Org structure attached to Jobs; read and written to keep reporting hierarchies aligned with an HRIS or warehouse. | Items is specific to Dynamo DB and Departments and Offices to Greenhouse — each maps to any object or custom field on the other side. | |
| Attributes Per-item fields, including nested maps and lists, flattened or mapped during sync. | Candidates Person records with contact details, tags, and custom fields; read and written via Harvest, often created from sourcing or enrichment pipelines. | Attributes is specific to Dynamo DB and Candidates to Greenhouse — each maps to any object or custom field on the other side. | |
| Partition and Sort Keys The primary key pair used as the match key for bi-directional sync. | Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. | Partition and Sort Keys is specific to Dynamo DB and Applications to Greenhouse — each maps to any object or custom field on the other side. | |
| Global Secondary Indexes Alternate access paths used when sync queries filter on non-key attributes. | Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. | Global Secondary Indexes is specific to Dynamo DB and Jobs to Greenhouse — each maps to any object or custom field on the other side. | |
| DynamoDB Streams Ordered item-level change records consumed for incremental sync. | Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. | DynamoDB Streams is specific to Dynamo DB and Offers to Greenhouse — each maps to any object or custom field on the other side. | |
| Global Tables Multi-region replicas relevant when syncs must read from a specific region. | Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. | Global Tables is specific to Dynamo DB and Scorecards to Greenhouse — each maps to any object or custom field on the other side. |
How changes propagate between Dynamo DB 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.
Dynamo DB Greenhouse Sub-second propagation
DetectionChanges in Dynamo DB are captured at the source via change data capture — no polling loop against its API. Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration.
DeliveryEach detected change is written to Greenhouse through its API, with automatic retries and rate-limit backoff.
Greenhouse Dynamo DB 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 Dynamo DB as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Dynamo DB: Throughput is governed by the table's provisioned or on-demand capacity mode.
- 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 Dynamo DB ⇄ Greenhouse
Connect Dynamo DB and Greenhouse for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dynamo DB–Greenhouse connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Dynamo DB 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 Dynamo DB or Greenhouse record.
Observability
Monitoring
Track your Dynamo DB ⇄ Greenhouse sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Dynamo DB and Greenhouse.
How the Dynamo DB and Greenhouse connectors work
Dynamo DB
- Integration surface
- Proprietary JSON-over-HTTPS API accessed through AWS SDKs; PartiQL supported for SQL-like queries
- Authentication
- AWS IAM credentials with SigV4 request signing
- Change detection
- Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration
- Capabilities
- read · write · CDC
- Rate limits
- Throughput is governed by the table's provisioned or on-demand capacity mode
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.
How it works
How to connect Dynamo DB 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.
- 01
Connect your apps
Authenticate Dynamo DB 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.
Dynamo DB
connected
Greenhouse
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Dynamo DB 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.
objects · Dynamo DB ⇄ GreenhouseCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Dynamo DB GreenhouseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Dynamo DB and Greenhouse integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Dynamo DB and Greenhouse: authenticate both systems, choose the objects to sync (such as Dynamo DB's Items and Attributes), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Dynamo DB and Greenhouse. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Dynamo DB: Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration. 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. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Dynamo DB side: Global Tables, Tables, Items, Attributes, plus custom fields where Dynamo DB exposes them. On the Greenhouse side: Scorecards, Scheduled Interviews, Users, Departments and Offices. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
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Common patterns for Dynamo DB and Greenhouse: Reporting and analytics on current data; Org and structure stay aligned; Computed and operational fields flow back. Scorecards, Scheduled Interviews, Users, Departments and Offices replicate into Dynamo DB where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.
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.
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:
Related integrations
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