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Database ⇄ Human resources

Amazon Aurora to BambooHR integration — real-time, two-way sync

Keep Amazon Aurora and BambooHR 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 Amazon Aurora and BambooHR

Put your workforce data where your apps can reach it: Amazon Aurora and BambooHR share the same people, positions, and org structure in real time.

BambooHR is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. Amazon Aurora is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Time Off, Employment Status, Departments and Divisions, Custom Tables in BambooHR need to exist as queryable Schemas, Tables, Views, Materialized Views in Amazon Aurora 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 Schemas, Tables, Views, Materialized Views in Amazon Aurora with Time Off, Employment Status, Departments and Divisions, Custom Tables in BambooHR field by field, in real time. You decide which system owns which fields — BambooHR 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 Offload sync reads to Aurora reader endpoints to avoid load on the writer instance.
  • 02 Two-way sync between Aurora application tables and a CRM so product data and account data stay consistent.
  • 03 Push approved Time Off into capacity and scheduling systems so project plans reflect real availability.
  • 04 Feed Compensation and custom-table data to a warehouse for HR analytics with field-level access control.

Common sync patterns

Mirror people records into the database

Records maintained in BambooHR land as queryable Schemas, Tables, Views, Materialized Views in Amazon Aurora, 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

Time Off, Employment Status, Departments and Divisions, Custom Tables replicate into Amazon Aurora where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.

What you can sync between Amazon Aurora and BambooHR

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.

Amazon Aurora objects BambooHR objects How this pairing syncs
Databases Logical databases within a cluster that scope a sync connection. Employment Status Effective-dated hire, leave, and termination status; drives automated provisioning and deprovisioning in downstream identity and license systems. Databases is specific to Amazon Aurora and Employment Status to BambooHR — each maps to any object or custom field on the other side.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Departments and Divisions Org-structure list values; synced to keep cost centers and team groupings consistent across ERP, identity, and analytics systems. Schemas is specific to Amazon Aurora and Departments and Divisions to BambooHR — each maps to any object or custom field on the other side.
Tables Relational tables synced bi-directionally at row level. Custom Tables Company-specific effective-dated tables (assets, training, certifications); rows read and written so custom HR data isn't trapped in the HRIS. Tables is specific to Amazon Aurora and Custom Tables to BambooHR — each maps to any object or custom field on the other side.
Views Read-only query-backed sources for downstream syncs. Reports Saved company reports retrievable via API; read out on a schedule to feed a warehouse without rebuilding field-by-field queries. Views is specific to Amazon Aurora and Reports to BambooHR — each maps to any object or custom field on the other side.
Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. Employees The core person record with personal and work fields; read out to identity, payroll, and IT systems, and written back from recruiting or onboarding tools. Materialized Views is specific to Amazon Aurora and Employees to BambooHR — each maps to any object or custom field on the other side.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. Job Information Effective-dated job title, department, division, location, and reporting line; synced so org charts and provisioning systems track internal moves. Columns and Data Types is specific to Amazon Aurora and Job Information to BambooHR — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora and BambooHR

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.

Amazon Aurora BambooHR Sub-second propagation

DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.

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

BambooHR Amazon Aurora Sub-second propagation

DetectionBambooHR notifies Stacksync of record changes through webhook events. The Get Updated Employee IDs endpoint (last-changed timestamps) returns employees inserted, updated, or deleted since a cursor for efficient polling.

DeliveryEach detected change is applied to Amazon Aurora as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
  • BambooHR: Requests are rate-limited per API key with standard REST throttling (429 on excess); bulk reads are best done through saved Reports or the updated-IDs delta endpoint rather than per-employee calls.
What ships with Amazon Aurora ⇄ BambooHR

Connect Amazon Aurora and BambooHR for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Aurora–BambooHR connection.

Real-time

Two-way sync

Changes in Amazon Aurora or BambooHR instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora or BambooHR 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 Amazon Aurora or BambooHR record.

Observability

Monitoring

Track your Amazon Aurora ⇄ BambooHR sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Aurora and BambooHR.

How the Amazon Aurora and BambooHR connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

BambooHR

Integration surface
BambooHR API (REST, per-company subdomain)
Authentication
API key per user over HTTP Basic auth (key as username), scoped to that user's permission level in BambooHR; OAuth/OpenID available for SSO-enabled apps
Change detection
The Get Updated Employee IDs endpoint (last-changed timestamps) returns employees inserted, updated, or deleted since a cursor for efficient polling; webhooks can fire on monitored field changes
Capabilities
read · write · webhooks
Rate limits
Requests are rate-limited per API key with standard REST throttling (429 on excess); bulk reads are best done through saved Reports or the updated-IDs delta endpoint rather than per-employee calls.
How it works

How to connect Amazon Aurora to BambooHR — 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 Amazon Aurora and BambooHR 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
    Amazon Aurora connected
    BambooHR connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon Aurora and BambooHR 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 · Amazon Aurora ⇄ BambooHR
    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
    Amazon Aurora BambooHR
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Aurora and BambooHR 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 342 integrations available for Amazon Aurora and BambooHR.

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