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Analytics ⇄ Data warehouse

Adobeanalytics to BigQuery integration — real-time data sync

Keep Adobeanalytics and BigQuery 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 Adobeanalytics and BigQuery

Flow Adobeanalytics data into BigQuery in real time — no exports, no schedulers, no custom scripts.

Adobeanalytics is a read-only source: Stacksync reads its data in real time and delivers it into BigQuery, so BigQuery always reflects the current state of Adobeanalytics — without exports, scripts, or schedulers.

Adobeanalytics is where teams explore, visualize, and report; BigQuery is the store of record that holds the raw tables and full history behind those views. The two overlap wherever the same events, users, and metrics matter to both, and when the bridge between them is a nightly export or a hand-built extract, dashboards lag the warehouse and analysts spend the morning arguing over whose number is right.

Common use cases

  • 01 Load report data on a schedule into a reporting database for executive dashboards without manual Analysis Workspace exports or Report Builder pulls.
  • 02 Sync Segment definitions into a marketing database so downstream tools target the same audiences Adobe Analytics computes.
  • 03 Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • 04 Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs

Common sync patterns

One number both sides agree on

Metrics and aggregates stay aligned between the two systems, so a figure shown in Adobeanalytics matches the BigQuery table it was built from instead of drifting between refreshes.

Where BigQuery holds the source tables: live data in the reporting layer

Records maintained in BigQuery flow into Adobeanalytics as they change, so dashboards and reports read current rows rather than an overnight extract.

Where Adobeanalytics produces segments or scores: results back to the warehouse

Cohorts, segments, and computed metrics defined in Adobeanalytics write to BigQuery as tables the rest of the stack can query and join.

What you can sync between Adobeanalytics and BigQuery

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.

Adobeanalytics objects BigQuery objects How this pairing syncs
Report Suites Report suite and virtual report suite configuration read via the /collections/suites endpoint; enumerated to list the report suites available to the company. Partitioned tables Synced like regular tables; partition columns map to target fields. Report Suites is specific to Adobeanalytics and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.
Users Users in the Analytics company, read via GET /users and /users/me; loaded for access, entitlement, and identity reconciliation reporting. Clustered tables Supported; clustering is transparent to the sync. Users is specific to Adobeanalytics and Clustered tables to BigQuery — each maps to any object or custom field on the other side.
Usage and Access Logs Admin audit and usage logs of report and tool activity, read via the usage/audit-log endpoints; loaded for security, governance, and adoption reporting. Datasets Organizational container — you pick which dataset’s tables to sync. Usage and Access Logs is specific to Adobeanalytics and Datasets to BigQuery — each maps to any object or custom field on the other side.
Reports Core reporting endpoint (POST /reports on analytics.adobe.io); returns ranked or trended report data for chosen metrics broken down by dimensions over a date range, with optional segment filters. The main dataset Stacksync reads out. Projects Connection scope: the service account grants access per project. Reports is specific to Adobeanalytics and Projects to BigQuery — each maps to any object or custom field on the other side.
Dimensions Available report dimensions (eVars, props, and standard dimensions) per report suite, read via GET /dimensions; pulled as reporting metadata to build report requests and mirror the model. Tables The syncable unit: only tables can be synced per the Stacksync docs. Dimensions is specific to Adobeanalytics and Tables to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and BigQuery

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.

Adobeanalytics BigQuery Interval-based propagation

DetectionStacksync polls Adobeanalytics for changes on an incremental schedule, reading only records changed since the previous pass. Pull-based over a date range: reports are requested for a from/to window and re-queried on a schedule.

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

BigQuery Adobeanalytics 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").

DeliveryAdobeanalytics does not accept inbound record writes, so this direction carries requests rather than records: Adobeanalytics's output flows back as field updates on the originating BigQuery records.

Rate-limit considerations

  • Adobeanalytics: The Analytics 2.0 API enforces 12 requests per 6 seconds (about 120 per minute) per user; exceeding it returns HTTP 429 with error_code 429050. A separate per-report-suite reporting-engine throttle can slow large requests without returning an error.
  • 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.
What ships with Adobeanalytics ⇄ BigQuery

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or BigQuery 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 Adobeanalytics or BigQuery record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Adobeanalytics and BigQuery connectors work

Adobeanalytics

Integration surface
Analytics 2.0 REST API on analytics.adobe.io for reporting and components; Data Feeds and Data Warehouse for raw hit-level export; Data Insertion and Bulk Data Insertion (CSV) APIs for inbound server-side collection.
Authentication
OAuth Server-to-Server via the Adobe Developer Console (JWT service-account auth was deprecated January 1, 2025). The company's global company ID is sent in the x-proxy-global-company-id header, and the integration needs at least the Report Suites, Metrics, and Dimensions permission groups.
Change detection
Pull-based over a date range: reports are requested for a from/to window and re-queried on a schedule. No change-data-capture feed or report-data webhooks; Adobe recommends not polling for new data faster than every 30 minutes and caching results.
Capabilities
read
Rate limits
The Analytics 2.0 API enforces 12 requests per 6 seconds (about 120 per minute) per user; exceeding it returns HTTP 429 with error_code 429050. A separate per-report-suite reporting-engine throttle can slow large requests without returning an error.

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
How it works

How to connect Adobeanalytics to BigQuery — 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 Adobeanalytics and BigQuery 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
    Adobeanalytics connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Adobeanalytics and BigQuery 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 473 integrations available for Adobeanalytics and BigQuery.

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