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Data warehouse ⇄ AI

Apache Druid to Autopilot integration — real-time, two-way sync

Keep Apache Druid and Autopilot 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 Apache Druid and Autopilot

Send the records Apache Druid holds into Autopilot for embedding, classification, and scoring, and land what Autopilot produces back in Apache Druid as new columns, one two-way connection instead of a batch job.

Apache Druid holds the raw records the business runs on; Autopilot turns those records into embeddings, scores, labels, and summaries. The two meet wherever a warehouse row needs to be enriched by a model and the result needs somewhere durable to live. Most teams stitch that meeting together with export scripts and a queue, then spend their time keeping the glue alive.

Stacksync syncs Custom Fields, Smart Segments, Journeys (Triggers), Activities in Autopilot with Tasks, Datasources, Segments, Dimensions in Apache Druid field by field, in real time, and in both directions. Rows added or changed in Apache Druid flow into Autopilot as they happen, and the Custom Fields, Smart Segments, Journeys (Triggers), Activities that Autopilot generates land back in Apache Druid as columns or tables, with field-level mapping and conflict rules in place of a custom pipeline.

The payoff is that model output stops living in a separate place from the data it describes. Once results sit in Apache Druid, they join against billing, product, and usage tables already there, so you can report on quality, cost, and coverage without moving anything by hand.

Common use cases

  • 01 Add contacts to a Journey from a database event or CRM stage change to start automated onboarding or nurture sequences.
  • 02 Mirror List and Smart Segment membership into a warehouse to power attribution and audience analytics alongside other sources.
  • 03 Sync Druid query results into a warehouse to combine real-time aggregates with historical models.
  • 04 Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.

Common sync patterns

Feed live warehouse records to Autopilot

Rows added or changed in Apache Druid flow into Autopilot within seconds, so embeddings, classifications, and enrichments are computed on current data rather than a nightly extract.

Model output back in the warehouse

Scores, labels, embeddings, or summaries produced in Autopilot land in Apache Druid as columns or tables, queryable and joinable with the rest of the business data.

Keep an index in step with the source

As records change in Apache Druid, matching Custom Fields, Smart Segments, Journeys (Triggers), Activities in Autopilot are inserted, updated, or removed, so what Autopilot serves reflects the warehouse instead of a stale snapshot.

What you can sync between Apache Druid and Autopilot

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.

Apache Druid objects Autopilot objects How this pairing syncs
Tasks Batch ingestion and compaction jobs monitored during data loads. Contacts Core people records (email, name, custom fields, list and segment membership); upserted two-way as the primary sync object. Tasks is specific to Apache Druid and Contacts to Autopilot — each maps to any object or custom field on the other side.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Lists Static contact lists; membership is readable per list and writable by adding or removing contacts. Datasources is specific to Apache Druid and Lists to Autopilot — each maps to any object or custom field on the other side.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Custom Fields User-defined contact properties (string, number, date, boolean); discovered so field keys map cleanly to destination columns. Segments is specific to Apache Druid and Custom Fields to Autopilot — each maps to any object or custom field on the other side.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Smart Segments Rule-based dynamic audiences; membership is computed by Autopilot, so it is read-only over the API. Dimensions is specific to Apache Druid and Smart Segments to Autopilot — each maps to any object or custom field on the other side.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Journeys (Triggers) Automation journeys; a contact can be added to a journey via its trigger endpoint to start automated email or SMS sequences. Metrics is specific to Apache Druid and Journeys (Triggers) to Autopilot — each maps to any object or custom field on the other side.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Activities Per-contact activity and event history (opens, clicks, journey steps); read-only feed used for engagement reporting. Ingestion Supervisors is specific to Apache Druid and Activities to Autopilot — each maps to any object or custom field on the other side.

How changes propagate between Apache Druid and Autopilot

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.

Apache Druid Autopilot 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.

DeliveryEach detected change is written to Autopilot through its API, with automatic retries and rate-limit backoff.

Autopilot Apache Druid Interval-based propagation

DetectionStacksync polls Autopilot for changes on an incremental schedule, reading only records changed since the previous pass. No CDC.

DeliveryEach detected change is applied to Apache Druid as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
  • Autopilot: The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
What ships with Apache Druid ⇄ Autopilot

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

Track your Apache Druid ⇄ Autopilot sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Druid and Autopilot.

How the Apache Druid and Autopilot connectors work

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

Autopilot

Integration surface
REST API (Autopilot v1); Autopilot rebranded to Ortto in 2021 and the newer Ortto API co-exists with the legacy Autopilot endpoints
Authentication
Per-account API key sent in the autopilotapikey request header (generated in account settings); requests use Content-Type application/json against https://api2.autopilothq.com/v1/
Change detection
No CDC; incremental sync polls the /contacts endpoint with bookmark cursor pagination and updated timestamps. Journey webhook actions can push specific contact events, but there is no general change-subscription webhook, so polling is the reliable path.
Capabilities
read · write
Rate limits
The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
Autopilot setup guide
How it works

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

    Choose tables

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

Apache Druid and Autopilot integration FAQ

SECURITY

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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 413 integrations available for Apache Druid and Autopilot.

Popular · 7 of 413
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