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Analytics ⇄ Database

Adobeanalytics to MongoDB integration — real-time data sync

Keep Adobeanalytics and MongoDB 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 MongoDB

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

Adobeanalytics is a read-only source: Stacksync reads its data in real time and delivers it into MongoDB, so MongoDB 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 MongoDB 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 Replicate operational MongoDB data into a relational database, flattening nested documents into normalized tables for SQL reporting.
  • 04 Capture change stream events and propagate them to SaaS tools in near real time instead of running batch exports.

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 MongoDB 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 MongoDB 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 MongoDB

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 MongoDB objects How this pairing syncs
Calculated Metrics User-defined derived metrics, read via GET /calculatedmetrics; mirrored so downstream tools reference the same calculated-metric definitions. Change streams The oplog-backed event feed that powers real-time change capture. Calculated Metrics is specific to Adobeanalytics and Change streams to MongoDB — each maps to any object or custom field on the other side.
Segments Saved segment definitions used to filter reports, read via GET /segments; cataloged and reused so downstream systems target the same audiences. GridFS files Chunked file storage whose metadata can be referenced by synced documents. Segments is specific to Adobeanalytics and GridFS files to MongoDB — each maps to any object or custom field on the other side.
Date Ranges Saved relative or rolling date ranges, read via GET /dateranges; read as reusable reporting components for report requests. Databases Logical groupings of collections that scope a sync connection. Date Ranges is specific to Adobeanalytics and Databases to MongoDB — 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. Collections The table-like sync unit; each collection maps to a table or object in the paired system. Report Suites is specific to Adobeanalytics and Collections to MongoDB — 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. Documents BSON records created, updated, and deleted during syncs, keyed by _id. Users is specific to Adobeanalytics and Documents to MongoDB — 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. Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. Usage and Access Logs is specific to Adobeanalytics and Embedded documents and arrays to MongoDB — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and MongoDB

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

MongoDB Adobeanalytics Sub-second propagation

DetectionChanges in MongoDB are captured at the source via change data capture — no polling loop against its API. MongoDB oplog and change streams (requires the database to run as a replica set — even single-node).

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 MongoDB 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 ⇄ MongoDB

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or MongoDB 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 MongoDB record.

Observability

Monitoring

Track your Adobeanalytics ⇄ MongoDB 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 MongoDB.

How the Adobeanalytics and MongoDB 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.

MongoDB

Integration surface
MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management
Authentication
Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required
Change detection
MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time
Capabilities
read · write · CDC
MongoDB setup guide
How it works

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

    Choose tables

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

Adobeanalytics and MongoDB 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.

Learn more about security
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ISO 27001
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CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

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 471 integrations available for Adobeanalytics and MongoDB.

Popular · 8 of 471
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