Real-time
Two-way sync
Changes in AWS Aurora PostgreSQL or Hibob instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Human resources
AWS Aurora PostgreSQL to Hibob integration — real-time, two-way sync
Keep AWS Aurora PostgreSQL and Hibob 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 AWS Aurora PostgreSQL and Hibob
Put your workforce data where your apps can reach it: AWS Aurora PostgreSQL and Hibob share the same people, positions, and org structure in real time.
Hibob is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. AWS Aurora PostgreSQL is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Salaries, Time off, Lifecycle, Documents in Hibob need to exist as queryable Tables, Rows, Columns, Primary keys and constraints in AWS Aurora PostgreSQL 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 Tables, Rows, Columns, Primary keys and constraints in AWS Aurora PostgreSQL with Salaries, Time off, Lifecycle, Documents in Hibob field by field, in real time. You decide which system owns which fields — Hibob 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 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
- 02 Feed operational dashboards from a read replica while the writer handles sync traffic.
- 03 Sync Time off requests and who's-out data into a scheduling or workforce-planning database for coverage and capacity reporting.
- 04 Two-way sync People (employee) profiles and Work records with a Postgres database so internal apps and directories read profiles in SQL while HR corrections flow back into Bob.
Common sync patterns
Org and structure stay aligned
Groups, departments, managers, and reporting lines from Hibob stay consistent in AWS Aurora PostgreSQL, so hierarchy-driven logic and permissions don't drift.
Computed and operational fields flow back
Values assembled or corrected in AWS Aurora PostgreSQL write onto the matching record in Hibob where those fields are writable, keeping the people system enriched.
Mirror people records into the database
Records maintained in Hibob land as queryable Tables, Rows, Columns, Primary keys and constraints in AWS Aurora PostgreSQL, so internal apps and dashboards read live data instead of a periodic export.
What you can sync between AWS Aurora PostgreSQL and Hibob
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.
| AWS Aurora PostgreSQL objects | Hibob objects | How this pairing syncs | |
|---|---|---|---|
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Time off Absence requests and who's-out data via /timeoff/employees/{id}/requests and /timeoff/whosout; submit new requests and read balances. | Databases and schemas is specific to AWS Aurora PostgreSQL and Time off to Hibob — each maps to any object or custom field on the other side. | |
| Tables The core sync unit; rows are matched across systems by primary key. | Lifecycle Hire, termination, and leave status changes at /people/{id}/lifecycle; read-only and the source of lifecycle webhook events. | Tables is specific to AWS Aurora PostgreSQL and Lifecycle to Hibob — each maps to any object or custom field on the other side. | |
| Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Documents Employee documents accessed under the Docs API; gated behind the Documents permission granted per service user. | Rows is specific to AWS Aurora PostgreSQL and Documents to Hibob — each maps to any object or custom field on the other side. | |
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Named lists Dropdown option lists such as departments and sites used to resolve field values when mapping People records during sync. | Columns is specific to AWS Aurora PostgreSQL and Named lists to Hibob — each maps to any object or custom field on the other side. | |
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | People (Employees) Core employee records with out-of-the-box and custom fields; read via POST /people/search, created and updated through the /people endpoints. | Primary keys and constraints is specific to AWS Aurora PostgreSQL and People (Employees) to Hibob — each maps to any object or custom field on the other side. | |
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Employment Historical table of job terms, contract, and working pattern under /people/{id}/employment; full CRUD, entries keyed by effectiveDate. | Views and materialized views is specific to AWS Aurora PostgreSQL and Employment to Hibob — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora PostgreSQL and Hibob
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.
AWS Aurora PostgreSQL Hibob Sub-second propagation
DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.
DeliveryEach detected change is written to Hibob through its API, with automatic retries and rate-limit backoff.
Hibob AWS Aurora PostgreSQL Sub-second propagation
DetectionHibob notifies Stacksync of record changes through webhook events. Webhooks fire for employee created/updated/deleted, table-entry created/updated, time off, and lifecycle events.
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Hibob: Rate limits are enforced per service user; violations return HTTP 429 with X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset response headers. The docs list POST /people/search at 50 requests per minute, and bulk /people/search is preferred over per-record reads.
What ships with AWS Aurora PostgreSQL ⇄ Hibob
Connect AWS Aurora PostgreSQL and Hibob for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Hibob connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora PostgreSQL or Hibob 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 AWS Aurora PostgreSQL or Hibob record.
Observability
Monitoring
Track your AWS Aurora PostgreSQL ⇄ Hibob sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Hibob.
How the AWS Aurora PostgreSQL and Hibob connectors work
AWS Aurora PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
- Capabilities
- read · write · CDC
Hibob
- Integration surface
- REST API (the Bob API)
- Authentication
- Service User credentials over HTTP Basic auth (Base64-encoded serviceUserId:serviceUserToken); permissions granted per data category (People, Payroll, Documents) in Bob admin
- Change detection
- Webhooks fire for employee created/updated/deleted, table-entry created/updated, time off, and lifecycle events; the employee.updated payload flags which fields changed and Bob recommends an API call for the full record. There is no CDC stream, and deleting a table entry fires no webhook (Bob has no table-entry deletion event).
- Capabilities
- read · write · webhooks
- Rate limits
- Rate limits are enforced per service user; violations return HTTP 429 with X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset response headers. The docs list POST /people/search at 50 requests per minute, and bulk /people/search is preferred over per-record reads.
How it works
How to connect AWS Aurora PostgreSQL to Hibob — 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 AWS Aurora PostgreSQL and Hibob with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
AWS Aurora PostgreSQL
connected
Hibob
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora PostgreSQL and Hibob 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 · AWS Aurora PostgreSQL ⇄ HibobCustomers 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.
AWS Aurora PostgreSQL HibobCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora PostgreSQL and Hibob integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and Hibob: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Databases and schemas and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and Hibob. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on AWS Aurora PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback. On Hibob: Webhooks fire for employee created/updated/deleted, table-entry created/updated, time off, and lifecycle events; the employee.updated payload flags which fields changed and Bob recommends an API call for the full record. There is no CDC stream, and deleting a table entry fires no webhook (Bob has no table-entry deletion event). Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the AWS Aurora PostgreSQL side: Tables, Rows, Columns, Primary keys and constraints, plus custom fields where AWS Aurora PostgreSQL exposes them. On the Hibob side: Salaries, Time off, Lifecycle, Documents. 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 AWS Aurora PostgreSQL and Hibob: Org and structure stay aligned; Computed and operational fields flow back; Mirror people records into the database. Groups, departments, managers, and reporting lines from Hibob stay consistent in AWS Aurora PostgreSQL, so hierarchy-driven logic and permissions don't drift.
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
Every pair below is a real-time, two-way sync. Search all 452 integrations available for AWS Aurora PostgreSQL and Hibob.
Popular · 7 of 452
-
AWS Aurora PostgreSQL ⇄ Paylocity -
AWS Aurora PostgreSQL ⇄ Ukg Ready -
AWS Aurora PostgreSQL ⇄ BambooHR -
Hibob ⇄ SQL Server -
Hibob ⇄ Postgres Heroku -
Hibob ⇄ Airtable - Hibob ⇄ AWS Aurora MySQL
No integrations match .
