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Analytics ⇄ Database

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

Keep Adobeanalytics and Google Cloud SQL 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 Google Cloud SQL

Give Adobeanalytics the users, events, and records that live in Google Cloud SQL in real time, and sync the cohorts and scores Adobeanalytics computes back into Google Cloud SQL where your applications read them.

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

A database holds the rows your business runs on: the users, events, orders, and records that every service reads and writes. Adobeanalytics is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from Google Cloud SQL into Adobeanalytics usually means a hand-built extract or a change-data-capture pipeline that breaks the moment a column is renamed, and reporting that always trails last night's load.

Common use cases

  • 01 Mirror Dimensions, Metrics, Calculated Metrics, and Segment definitions into a catalog database to document the Adobe Analytics reporting model.
  • 02 Load report data on a schedule into a reporting database for executive dashboards without manual Analysis Workspace exports or Report Builder pulls.
  • 03 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • 04 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.

Common sync patterns

One version of each user or account

A user, account, or record corrected in either system updates the other, so the identity your reports group by matches the identity your database stores.

Filter and grouping dimensions kept fresh

Attributes teams slice by, such as plan, region, or account owner, stay current in Adobeanalytics because they sync from Google Cloud SQL as they change, instead of going stale after a one-time import.

Where Adobeanalytics tracks product events: behavior onto stored records

Signup, usage, and lifecycle events captured in Adobeanalytics sync into Google Cloud SQL as rows, so applications and internal tools can read behavioral data next to the records they already keep.

What you can sync between Adobeanalytics and Google Cloud SQL

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 SQL 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. Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. Users is specific to Adobeanalytics and Instances to Google Cloud SQL — 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. Databases Scope the tables included in a sync configuration. Usage and Access Logs is specific to Adobeanalytics and Databases to Google Cloud SQL — 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. Schemas Namespace tables in PostgreSQL and SQL Server instances. Reports is specific to Adobeanalytics and Schemas to Google Cloud SQL — 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 Mapped directly to sync targets; schema changes can be propagated. Dimensions is specific to Adobeanalytics and Tables to Google Cloud SQL — 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. Rows Read and written by primary key during each sync cycle. Metrics is specific to Adobeanalytics and Rows to Google Cloud SQL — 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. Views Read-only sources for shaping data before syncing it out. Calculated Metrics is specific to Adobeanalytics and Views to Google Cloud SQL — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and Google Cloud SQL

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 SQL 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 SQL as a row-level write, with types converted between the two schemas.

Google Cloud SQL Adobeanalytics Sub-second propagation

DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.

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 SQL 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 SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with Adobeanalytics ⇄ Google Cloud SQL

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

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

Real-time

Real-time sync

Changes in Adobeanalytics or Google Cloud SQL 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 SQL 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 SQL record.

Observability

Monitoring

Track your Adobeanalytics ⇄ Google Cloud SQL 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 SQL.

How the Adobeanalytics and Google Cloud SQL 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 SQL

Integration surface
Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management
Authentication
Database credentials; IAM database authentication is available for MySQL and PostgreSQL
Change detection
Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Constrained by instance size and connection limits rather than API quotas.
How it works

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

    Choose tables

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

Adobeanalytics and Google Cloud SQL 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 366 integrations available for Adobeanalytics and Google Cloud SQL.

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