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Analytics ⇄ Database

Adobeanalytics to AWS Aurora MySQL integration — real-time data sync

Keep Adobeanalytics and AWS Aurora MySQL 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 AWS Aurora MySQL

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

Adobeanalytics is a read-only source: Stacksync reads its data in real time and delivers it into AWS Aurora MySQL, so AWS Aurora MySQL 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 AWS Aurora MySQL 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 Sync Segment definitions into a marketing database so downstream tools target the same audiences Adobe Analytics computes.
  • 02 Read Users and Usage/Audit logs into a security or governance database for access reviews and tool-usage reporting across the Analytics company.
  • 03 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
  • 04 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.

Common sync patterns

Analytics on live operational data, minus the pipeline

The users, events, orders, and records stored in AWS Aurora MySQL land in Adobeanalytics as they change, so dashboards, funnels, and metrics run on current data instead of last night's extract.

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 AWS Aurora MySQL as they change, instead of going stale after a one-time import.

What you can sync between Adobeanalytics and AWS Aurora MySQL

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 AWS Aurora MySQL objects How this pairing syncs
Date Ranges Saved relative or rolling date ranges, read via GET /dateranges; read as reusable reporting components for report requests. Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Date Ranges is specific to Adobeanalytics and Rows to AWS Aurora MySQL — each maps to any object or custom field on the other side.
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. Columns MySQL data types are mapped to the paired system's field types during schema setup. Report Suites is specific to Adobeanalytics and Columns to AWS Aurora MySQL — 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. Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Users is specific to Adobeanalytics and Primary keys and indexes to AWS Aurora MySQL — 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. Views Can serve as read-only sync sources for derived or filtered datasets. Usage and Access Logs is specific to Adobeanalytics and Views to AWS Aurora MySQL — 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. Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Reports is specific to Adobeanalytics and Foreign keys to AWS Aurora MySQL — 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. Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Dimensions is specific to Adobeanalytics and Stored procedures and triggers to AWS Aurora MySQL — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and AWS Aurora MySQL

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 AWS Aurora MySQL 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 AWS Aurora MySQL as a row-level write, with types converted between the two schemas.

AWS Aurora MySQL Adobeanalytics Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

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 AWS Aurora MySQL 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.
What ships with Adobeanalytics ⇄ AWS Aurora MySQL

Connect Adobeanalytics and AWS Aurora MySQL for flexible, real-time data sync.

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or AWS Aurora MySQL 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 AWS Aurora MySQL record.

Observability

Monitoring

Track your Adobeanalytics ⇄ AWS Aurora MySQL 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 AWS Aurora MySQL.

How the Adobeanalytics and AWS Aurora MySQL 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.

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
Capabilities
read · write · CDC
How it works

How to connect Adobeanalytics to AWS Aurora MySQL — 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 AWS Aurora MySQL 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
    AWS Aurora MySQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Adobeanalytics and AWS Aurora MySQL 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 ⇄ AWS Aurora MySQL
    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 AWS Aurora MySQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Adobeanalytics and AWS Aurora MySQL 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 381 integrations available for Adobeanalytics and AWS Aurora MySQL.

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