Skip to content
Analytics ⇄ Database

Adobeanalytics to Neo4j integration — real-time data sync

Keep Adobeanalytics and Neo4j in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Adobeanalytics and Neo4j

Give Adobeanalytics the users, events, and records that live in Neo4j in real time, and sync the cohorts and scores Adobeanalytics computes back into Neo4j where your applications read them.

Adobeanalytics is a read-only source: Stacksync reads its data in real time and delivers it into Neo4j, so Neo4j 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 Neo4j 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 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 Sync product catalog and order history into Neo4j to power recommendation queries.
  • 04 Feed identity and access data into a graph for entitlement and blast-radius analysis.

Common sync patterns

Analytics on live operational data, minus the pipeline

The users, events, orders, and records stored in Neo4j 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 Neo4j as they change, instead of going stale after a one-time import.

What you can sync between Adobeanalytics and Neo4j

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 Neo4j objects How this pairing syncs
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. Properties Key-value attributes on both nodes and relationships, mapped from source fields. Dimensions is specific to Adobeanalytics and Properties to Neo4j — 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. Labels Node type markers used to map source tables or objects onto the graph. Metrics is specific to Adobeanalytics and Labels to Neo4j — 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. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Calculated Metrics is specific to Adobeanalytics and Indexes & Constraints to Neo4j — 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. Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Segments is specific to Adobeanalytics and Databases to Neo4j — 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. Users & Roles Security principals controlling what an integration credential can query or modify. Date Ranges is specific to Adobeanalytics and Users & Roles to Neo4j — 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. Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Report Suites is specific to Adobeanalytics and Nodes to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and Neo4j

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 Neo4j 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 written to Neo4j through its API, with automatic retries and rate-limit backoff.

Neo4j Adobeanalytics Sub-second propagation

DetectionChanges in Neo4j are captured at the source via change data capture — no polling loop against its API. Neo4j Change Data Capture on Enterprise and Aura streams graph changes.

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 Neo4j 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 ⇄ Neo4j

Connect Adobeanalytics and Neo4j for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Adobeanalytics–Neo4j connection.

Real-time

Real-time sync

Changes in Adobeanalytics or Neo4j instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or Neo4j 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 Neo4j record.

Observability

Monitoring

Track your Adobeanalytics ⇄ Neo4j 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 Neo4j.

How the Adobeanalytics and Neo4j 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.

Neo4j

Integration surface
Bolt binary protocol with Cypher via official drivers, plus an HTTP query API
Authentication
Username/password (basic auth); enterprise deployments add SSO options
Change detection
Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties
Capabilities
read · write · CDC
How it works

How to connect Adobeanalytics to Neo4j — 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 Neo4j 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
    Neo4j connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Adobeanalytics and Neo4j 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 ⇄ Neo4j
    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 Neo4j
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Adobeanalytics and Neo4j 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
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
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 448 integrations available for Adobeanalytics and Neo4j.

Popular · 8 of 448
All Adobeanalytics integrations All Neo4j integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own