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Database ⇄ Human resources

AWS Aurora MySQL to Hibob integration — real-time, two-way sync

Keep AWS Aurora MySQL 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.

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Why teams connect AWS Aurora MySQL and Hibob

Put your workforce data where your apps can reach it: AWS Aurora MySQL 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 MySQL is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Named lists, People (Employees), Employment, Work in Hibob need to exist as queryable Columns, Primary keys and indexes, Views, Foreign keys in AWS Aurora MySQL 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 Columns, Primary keys and indexes, Views, Foreign keys in AWS Aurora MySQL with Named lists, People (Employees), Employment, Work 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 Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
  • 02 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
  • 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 MySQL, so hierarchy-driven logic and permissions don't drift.

Computed and operational fields flow back

Values assembled or corrected in AWS Aurora MySQL 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 Columns, Primary keys and indexes, Views, Foreign keys in AWS Aurora MySQL, so internal apps and dashboards read live data instead of a periodic export.

What you can sync between AWS Aurora MySQL 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 MySQL objects Hibob objects How this pairing syncs
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Salaries Compensation history at /people/{id}/salaries; full CRUD but gated behind the Payroll permission on the service user. Stored procedures and triggers is specific to AWS Aurora MySQL and Salaries to Hibob — each maps to any object or custom field on the other side.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Time off Absence requests and who's-out data via /timeoff/employees/{id}/requests and /timeoff/whosout; submit new requests and read balances. Databases (schemas) is specific to AWS Aurora MySQL and Time off to Hibob — each maps to any object or custom field on the other side.
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. 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 MySQL and Lifecycle to Hibob — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Documents Employee documents accessed under the Docs API; gated behind the Documents permission granted per service user. Rows is specific to AWS Aurora MySQL and Documents to Hibob — each maps to any object or custom field on the other side.
Columns MySQL data types are mapped to the paired system's field types during schema setup. 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 MySQL and Named lists to Hibob — each maps to any object or custom field on the other side.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. 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 indexes is specific to AWS Aurora MySQL and People (Employees) to Hibob — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL 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 MySQL Hibob Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

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

Hibob AWS Aurora MySQL 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 MySQL 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 MySQL ⇄ Hibob

Connect AWS Aurora MySQL and Hibob for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–Hibob connection.

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Hibob instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora MySQL 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 MySQL or Hibob record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ 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 MySQL and Hibob.

How the AWS Aurora MySQL and Hibob connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns 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.
Hibob setup guide
How it works

How to connect AWS Aurora MySQL 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.

  1. 01

    Connect your apps

    Authenticate AWS Aurora MySQL 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    AWS Aurora MySQL connected
    Hibob connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · AWS Aurora MySQL ⇄ Hibob
    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
    AWS Aurora MySQL Hibob
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL and Hibob 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 450 integrations available for AWS Aurora MySQL and Hibob.

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