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Analytics ⇄ Data warehouse

Adobeanalytics to Apache Druid integration — real-time data sync

Keep Adobeanalytics and Apache Druid 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 Apache Druid

Flow Adobeanalytics data into Apache Druid 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 Apache Druid, so Apache Druid always reflects the current state of Adobeanalytics — without exports, scripts, or schedulers.

Adobeanalytics is where teams explore, visualize, and report; Apache Druid 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 Pull ranked and trended Reports (metrics by dimension) into Postgres or a warehouse so web and marketing analytics join with CRM, ad-spend, and revenue data in SQL.
  • 02 Mirror Dimensions, Metrics, Calculated Metrics, and Segment definitions into a catalog database to document the Adobe Analytics reporting model.
  • 03 Expose product telemetry stored in Druid to business tools without granting direct cluster access.
  • 04 Query aggregated event metrics from Druid and sync them into CRM account fields for usage-based selling.

Common sync patterns

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 Apache Druid table it was built from instead of drifting between refreshes.

Where Apache Druid holds the source tables: live data in the reporting layer

Records maintained in Apache Druid flow into Adobeanalytics as they change, so dashboards and reports read current rows rather than an overnight extract.

What you can sync between Adobeanalytics and Apache Druid

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 Apache Druid 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. Dimensions String and categorical columns used for filtering and grouping in synced queries. Same entity on both sides — records pair one-to-one and field-level changes reconcile in the writable direction.
Metrics Standard metrics available for a report suite, read via GET /metrics; read as metadata to construct report requests and document available measures. Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Same entity on both sides — records pair one-to-one and field-level changes reconcile in the writable direction.
Segments Saved segment definitions used to filter reports, read via GET /segments; cataloged and reused so downstream systems target the same audiences. Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Same entity on both sides — records pair one-to-one and field-level changes reconcile in the writable direction.
Users Users in the Analytics company, read via GET /users and /users/me; loaded for access, entitlement, and identity reconciliation reporting. Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Users is specific to Adobeanalytics and Datasources to Apache Druid — 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. Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Usage and Access Logs is specific to Adobeanalytics and Ingestion Supervisors to Apache Druid — 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. Lookups Key-value mappings joined at query time, refreshable from external systems. Reports is specific to Adobeanalytics and Lookups to Apache Druid — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and Apache Druid

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

Apache Druid Adobeanalytics Interval-based propagation

DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.

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 Apache Druid 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.
  • Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
What ships with Adobeanalytics ⇄ Apache Druid

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or Apache Druid 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 Apache Druid record.

Observability

Monitoring

Track your Adobeanalytics ⇄ Apache Druid 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 Apache Druid.

How the Adobeanalytics and Apache Druid 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.

Apache Druid

Integration surface
REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
Authentication
Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
Change detection
Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
Capabilities
read · write
Rate limits
No fixed API quotas; query concurrency is bounded by broker and historical node capacity
How it works

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

    Choose tables

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

Adobeanalytics and Apache Druid integration FAQ

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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 371 integrations available for Adobeanalytics and Apache Druid.

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