Skip to content
Database ⇄ Security and identity

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

Keep AWS Aurora MySQL and Jumpcloud 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 MySQL and Jumpcloud

Close the gap between your application data and your directory: AWS Aurora MySQL and Jumpcloud share users, groups, and access in real time, in both directions.

Jumpcloud is the system of record for who people are and what they can reach: users, the groups they belong to, and the applications assigned to them. AWS Aurora MySQL holds the operational data those same people show up in, whether an employee or member table that decides who should have an account at all, a customers list, or the rows an application checks before it authorizes an action. The two describe overlapping users and groups, and when a nightly export or a hand-run script is all that connects them, accounts lag joiners and leavers and the application authorizes against a stale picture of who has access.

Stacksync syncs Rows, Columns, Primary keys and indexes, Views in AWS Aurora MySQL with User Groups, Systems (devices), System Groups, Applications (SSO) in Jumpcloud field by field, in real time, and in both directions. You decide which system owns which fields, with the directory holding credentials and group membership and the database holding the source list of people who should exist at all, and Stacksync keeps every copy consistent, resolving conflicts by rules you set. A person added to a table becomes an account within seconds, a departure disables one just as fast, and the directory's users and groups are always present in your tables as ordinary rows.

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 Read Systems and System Group memberships into a database for device inventory, patch reporting, and conditional-access analysis.
  • 04 Drive Application and Policy assignments from HR attributes or entitlement tables so SSO access and device policies change the moment a role does.

Common sync patterns

One profile, kept current

A name, department, email, or manager corrected in either system updates the other, so the profile the directory shows and the data the application reads stop drifting apart.

Provision accounts from the source of truth

When a person is added to the employee, member, or customer table in AWS Aurora MySQL, Stacksync creates the matching user in Jumpcloud with the right attributes, so access starts from live data instead of a manual ticket.

Deprovision the moment the record changes

When someone is marked inactive or removed in AWS Aurora MySQL, the matching account in Jumpcloud is disabled within seconds, closing the window between a departure and a login that still works.

What you can sync between AWS Aurora MySQL and Jumpcloud

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 Jumpcloud objects How this pairing syncs
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Applications (SSO) SAML and OIDC SSO app configs; read via v2 /applications and their user/group assignments created and removed to control who can reach each connected app. Databases (schemas) is specific to AWS Aurora MySQL and Applications (SSO) to Jumpcloud — 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. Policies Device configuration and MDM policies; read, created from templates, and updated via v2 /policies, then bound to systems and system groups to enforce settings across the fleet. Tables is specific to AWS Aurora MySQL and Policies to Jumpcloud — 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. Commands Scripts and commands run on managed systems; full CRUD via v1 /commands, then triggered on target systems and groups for automation and remediation. Rows is specific to AWS Aurora MySQL and Commands to Jumpcloud — 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. Directory Insights events Audit stream of logins and admin actions across SSO, LDAP, RADIUS, systems, and MDM; read-only, queried by POST and used as the change feed and SIEM source. Columns is specific to AWS Aurora MySQL and Directory Insights events to Jumpcloud — 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. System Users (Users) Directory user accounts (email, username, attributes, status, MFA, group and app bindings); full CRUD via the v1 /systemusers API - create, update, activate or suspend, and delete to match an HR or identity source. Primary keys and indexes is specific to AWS Aurora MySQL and System Users (Users) to Jumpcloud — each maps to any object or custom field on the other side.
Views Can serve as read-only sync sources for derived or filtered datasets. User Groups User groups that grant app, LDAP, and RADIUS access; created, updated, and deleted via v2 /usergroups, with membership managed through the graph association endpoints. Views is specific to AWS Aurora MySQL and User Groups to Jumpcloud — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL and Jumpcloud

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 Jumpcloud 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 Jumpcloud through its API, with automatic retries and rate-limit backoff.

Jumpcloud AWS Aurora MySQL Sub-second propagation

DetectionJumpcloud notifies Stacksync of record changes through webhook events. No database-style change log.

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

Rate-limit considerations

  • Jumpcloud: JumpCloud rate-limits API requests and returns HTTP 429 (Rate limit exceeded) when a client sends requests too quickly; its guidance is to back off and retry at a lower rate. Specific per-minute ceilings are not published, and the Directory Insights API is metered separately. Webhook deliveries are retried three times with exponential backoff on 5xx, 408, or 429 responses.
What ships with AWS Aurora MySQL ⇄ Jumpcloud

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

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

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Jumpcloud 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 Jumpcloud 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 Jumpcloud record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Jumpcloud 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 Jumpcloud.

How the AWS Aurora MySQL and Jumpcloud 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

Jumpcloud

Integration surface
JumpCloud REST API - v1 (console.jumpcloud.com/api) for Systems, System Users, and Commands; v2 (/api/v2) for User Groups, System Groups, Applications, Policies, and resource associations; plus the Directory Insights API (api.jumpcloud.com/insights/directory/v1/events) and Webhook Channels for outbound events.
Authentication
Admin API key sent in the x-api-key header (keys are prefixed jca_, generated in the console with a 30-365 day expiry, and disabled for admins by default until enabled); an x-org-id header scopes calls to a single organization for MSP multi-tenant admins. System Context authorization (HMAC-signed) also exists for agent-run calls.
Change detection
No database-style change log. The Directory Insights API is queried by POST for login and admin events across SSO, LDAP, RADIUS, systems, MDM, and directory services - including the association_change event that records user-to-group and policy-to-device membership changes; Webhook Channels tied to Insights Rules POST JSON to a registered endpoint for near-real-time triggers.
Capabilities
read · write · webhooks
Rate limits
JumpCloud rate-limits API requests and returns HTTP 429 (Rate limit exceeded) when a client sends requests too quickly; its guidance is to back off and retry at a lower rate. Specific per-minute ceilings are not published, and the Directory Insights API is metered separately. Webhook deliveries are retried three times with exponential backoff on 5xx, 408, or 429 responses.
How it works

How to connect AWS Aurora MySQL to Jumpcloud — 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 Jumpcloud 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
    Jumpcloud connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL and Jumpcloud 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 ⇄ Jumpcloud
    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 Jumpcloud
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

AWS Aurora MySQL and Jumpcloud 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.

Learn more about security
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:

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 448 integrations available for AWS Aurora MySQL and Jumpcloud.

Popular · 8 of 448
All AWS Aurora MySQL integrations All Jumpcloud integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own