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Database ⇄ Security and identity

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

Keep AWS Aurora PostgreSQL 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.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect AWS Aurora PostgreSQL and Jumpcloud

Close the gap between your application data and your directory: AWS Aurora PostgreSQL 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 PostgreSQL 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 Databases and schemas, Tables, Rows, Columns in AWS Aurora PostgreSQL with Policies, Commands, Directory Insights events, System Users (Users) 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 Sync JSONB-heavy application data into structured objects in downstream business systems.
  • 02 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
  • 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

Deprovision the moment the record changes

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

Read users and groups as ordinary tables

Users, groups, and their memberships from Jumpcloud land in AWS Aurora PostgreSQL as rows your application and queries can join, so authorization checks and access reporting run against the database instead of the directory API.

Keep group and role membership aligned

A group or role change made in either system updates the other, so the entitlements an application enforces match what the directory grants.

What you can sync between AWS Aurora PostgreSQL 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 PostgreSQL objects Jumpcloud objects How this pairing syncs
Tables The core sync unit; rows are matched across systems by primary key. 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. Tables is specific to AWS Aurora PostgreSQL and System Users (Users) to Jumpcloud — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. 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. Rows is specific to AWS Aurora PostgreSQL and User Groups to Jumpcloud — 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. Systems (devices) Enrolled macOS, Windows, and Linux machines running the JumpCloud agent; agent-enrolled, so the API reads, updates, and deletes systems for inventory and management rather than creating them. Columns is specific to AWS Aurora PostgreSQL and Systems (devices) to Jumpcloud — 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. System Groups Device groups used to scope policies, commands, and access; full CRUD via v2 /systemgroups, with systems bound and unbound through association endpoints. Primary keys and constraints is specific to AWS Aurora PostgreSQL and System Groups to Jumpcloud — 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. 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. Views and materialized views is specific to AWS Aurora PostgreSQL and Applications (SSO) to Jumpcloud — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. 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. Foreign keys is specific to AWS Aurora PostgreSQL and Policies to Jumpcloud — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL 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 PostgreSQL Jumpcloud 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 Jumpcloud through its API, with automatic retries and rate-limit backoff.

Jumpcloud AWS Aurora PostgreSQL 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 PostgreSQL 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 PostgreSQL ⇄ Jumpcloud

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

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

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL 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 PostgreSQL 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 PostgreSQL or Jumpcloud record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ 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 PostgreSQL and Jumpcloud.

How the AWS Aurora PostgreSQL and Jumpcloud 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

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 PostgreSQL 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 PostgreSQL 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 PostgreSQL connected
    Jumpcloud connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL 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 PostgreSQL ⇄ 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 PostgreSQL Jumpcloud
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora PostgreSQL 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.

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→ 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 450 integrations available for AWS Aurora PostgreSQL and Jumpcloud.

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