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Analytics ⇄ Data warehouse

Adobeanalytics to Google Cloud Platform integration — real-time data sync

Keep Adobeanalytics and Google Cloud Platform 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 Adobeanalytics and Google Cloud Platform

Flow Adobeanalytics data into Google Cloud Platform 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 Google Cloud Platform, so Google Cloud Platform always reflects the current state of Adobeanalytics — without exports, scripts, or schedulers.

Adobeanalytics is where teams explore, visualize, and report; Google Cloud Platform 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 Publish change events to Pub/Sub so downstream services react to record updates as they happen.

Common sync patterns

Shared user and account keys

Users and accounts tracked in Adobeanalytics line up with the customer or user rows in Google Cloud Platform on a stable key, so both sides count the same population.

Corrections propagate instead of reloading

When a record is fixed or backfilled on one side, the change reaches the other without a full reload, keeping history consistent across both.

One number both sides agree on

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

What you can sync between Adobeanalytics and Google Cloud Platform

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 Google Cloud Platform objects How this pairing syncs
Users Users in the Analytics company, read via GET /users and /users/me; loaded for access, entitlement, and identity reconciliation reporting. Pub/Sub topics Event streams used to move change events between systems in near real time. Users is specific to Adobeanalytics and Pub/Sub topics to Google Cloud Platform — 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. Firestore documents Document data read and written through the Firestore API for app-facing syncs. Usage and Access Logs is specific to Adobeanalytics and Firestore documents to Google Cloud Platform — 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. Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. Reports is specific to Adobeanalytics and Spanner tables to Google Cloud Platform — 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. BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. Dimensions is specific to Adobeanalytics and BigQuery datasets to Google Cloud Platform — each maps to any object or custom field on the other side.
Metrics Standard metrics available for a report suite, read via GET /metrics; read as metadata to construct report requests and document available measures. BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. Metrics is specific to Adobeanalytics and BigQuery tables to Google Cloud Platform — each maps to any object or custom field on the other side.
Calculated Metrics User-defined derived metrics, read via GET /calculatedmetrics; mirrored so downstream tools reference the same calculated-metric definitions. Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. Calculated Metrics is specific to Adobeanalytics and Cloud SQL databases to Google Cloud Platform — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and Google Cloud Platform

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 Google Cloud Platform 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 Google Cloud Platform as a row-level write, with types converted between the two schemas.

Google Cloud Platform Adobeanalytics Sub-second propagation

DetectionGoogle Cloud Platform pushes changes as they happen — webhook events backed by change data capture. Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery.

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 Google Cloud Platform 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.
  • Google Cloud Platform: Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits.
What ships with Adobeanalytics ⇄ Google Cloud Platform

Connect Adobeanalytics and Google Cloud Platform for flexible, real-time data sync.

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or Google Cloud Platform 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 Google Cloud Platform record.

Observability

Monitoring

Track your Adobeanalytics ⇄ Google Cloud Platform 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 Google Cloud Platform.

How the Adobeanalytics and Google Cloud Platform 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.

Google Cloud Platform

Integration surface
Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols
Authentication
IAM service accounts with OAuth 2.0 tokens
Change detection
Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery tables
Capabilities
read · write · CDC · webhooks
Rate limits
Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits
How it works

How to connect Adobeanalytics to Google Cloud Platform — 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 Google Cloud Platform 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
    Google Cloud Platform connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Adobeanalytics and Google Cloud Platform 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 ⇄ Google Cloud Platform
    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 Google Cloud Platform
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Adobeanalytics and Google Cloud Platform 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 470 integrations available for Adobeanalytics and Google Cloud Platform.

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