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Data warehouse ⇄ Security and identity

BigQuery to Jumpcloud integration — real-time, two-way sync

Keep BigQuery 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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Why teams connect BigQuery and Jumpcloud

Land the users, groups, and access events from Jumpcloud in BigQuery continuously for security analytics, and write computed results back — without building or maintaining a pipeline.

Jumpcloud is the record of who exists and what they can reach; BigQuery is where the business measures everything else. The two overlap on people and their access — the same users, groups, roles, and events that Jumpcloud governs are what security, compliance, and analytics teams want to query in BigQuery. Getting them there usually means a brittle export that runs overnight and hands auditors a snapshot that is already out of date.

Stacksync syncs User Groups, Systems (devices), System Groups, Applications (SSO) from Jumpcloud into tables in BigQuery in real time, and the connection works in both directions: values computed in BigQuery, such as risk scores or access-review decisions, can be written back to attributes in Jumpcloud where the identity team acts on them. Schema changes are handled, API limits are managed, and the sync is something you configure rather than a pipeline you keep alive.

Common use cases

  • 01 Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
  • 02 Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • 03 Drive Application and Policy assignments from HR attributes or entitlement tables so SSO access and device policies change the moment a role does.
  • 04 Two-way sync User Groups and their memberships between JumpCloud and a source-of-truth database so app, LDAP, and RADIUS access stays aligned with org data.

Common sync patterns

Directory data in the warehouse, minus the pipeline

Users, groups, and roles from Jumpcloud arrive in BigQuery as queryable tables, current within seconds instead of a nightly directory export.

Access and sign-in analytics

Sign-in and access events from Jumpcloud land in BigQuery, so security and compliance teams can query who reached what, and when, alongside the rest of the business's data.

Access governance on joined data

Join Jumpcloud's users and group memberships with HR, product, and usage data already in BigQuery to surface who holds access they no longer need.

What you can sync between BigQuery 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.

BigQuery objects Jumpcloud objects How this pairing syncs
Tables The syncable unit: only tables can be synced per the Stacksync docs. 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. Tables is specific to BigQuery and User Groups to Jumpcloud — each maps to any object or custom field on the other side.
Partitioned tables Synced like regular tables; partition columns map to target 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. Partitioned tables is specific to BigQuery and Systems (devices) to Jumpcloud — each maps to any object or custom field on the other side.
Clustered tables Supported; clustering is transparent to the sync. System Groups Device groups used to scope policies, commands, and access; full CRUD via v2 /systemgroups, with systems bound and unbound through association endpoints. Clustered tables is specific to BigQuery and System Groups to Jumpcloud — each maps to any object or custom field on the other side.
Datasets Organizational container — you pick which dataset’s tables to sync. 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. Datasets is specific to BigQuery and Applications (SSO) to Jumpcloud — each maps to any object or custom field on the other side.
Projects Connection scope: the service account grants access per project. 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. Projects is specific to BigQuery and Policies to Jumpcloud — each maps to any object or custom field on the other side.

How changes propagate between BigQuery 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.

BigQuery Jumpcloud Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

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

Jumpcloud BigQuery Sub-second propagation

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

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

Rate-limit considerations

  • BigQuery: Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes.
  • 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 BigQuery ⇄ Jumpcloud

Connect BigQuery and Jumpcloud for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in BigQuery or Jumpcloud instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery 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 BigQuery or Jumpcloud record.

Observability

Monitoring

Track your BigQuery ⇄ Jumpcloud sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between BigQuery and Jumpcloud.

How the BigQuery and Jumpcloud connectors work

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide

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

    Choose tables

    Pick the BigQuery 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 · BigQuery ⇄ 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
    BigQuery Jumpcloud
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

BigQuery 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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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 540 integrations available for BigQuery and Jumpcloud.

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