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Data warehouse ⇄ CRM

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

Keep Apache Druid and Outreach 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Apache Druid and Outreach

Sync Outreach into Apache Druid continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. Users, Mailboxes, Prospects, Accounts from Outreach land in Apache Druid as live tables, updated within seconds, and columns computed in Apache Druid write back to fields in Outreach. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Keep account ownership and stages aligned between Outreach and the CRM as territories change.
  • 02 Suppress prospects across systems when a contact unsubscribes or a customer churns.
  • 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

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Apache Druid appear as fields in Outreach, where the people working accounts actually see them.

A single customer view

Join Outreach's relationship data with billing, product, and support data in Apache Druid to build the customer picture the CRM alone cannot hold.

Cleanup that sticks

Deduplication and normalization done in Apache Druid can be written back, so warehouse-side cleanup actually fixes the CRM.

What you can sync between Apache Druid and Outreach

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 Outreach objects How this pairing syncs
Tasks Batch ingestion and compaction jobs monitored during data loads. Tasks Rep action items mirrored between Outreach and the CRM Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Accounts Companies grouping prospects, aligned with CRM account ownership Dimensions is specific to Apache Druid and Accounts to Outreach — each maps to any object or custom field on the other side.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Sequences Multi-step cadences; synced as reference data for enrollment automation Metrics is specific to Apache Druid and Sequences to Outreach — 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. Sequence states Per-prospect enrollments; writing one adds a prospect to a cadence Ingestion Supervisors is specific to Apache Druid and Sequence states to Outreach — each maps to any object or custom field on the other side.
Lookups Key-value mappings joined at query time, refreshable from external systems. Mailings Sent emails with engagement data, pulled for activity analytics Lookups is specific to Apache Druid and Mailings to Outreach — 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. Calls Logged call records synced into engagement reporting Datasources is specific to Apache Druid and Calls to Outreach — each maps to any object or custom field on the other side.

How changes propagate between Apache Druid and Outreach

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 Outreach 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 Outreach through its API, with automatic retries and rate-limit backoff.

Outreach Apache Druid Sub-second propagation

DetectionOutreach notifies Stacksync of record changes through webhook events. Webhook subscriptions on resource create, update, and destroy events, plus polling.

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.
  • Outreach: Subject to per-user hourly rate limits.
What ships with Apache Druid ⇄ Outreach

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Outreach 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 Outreach record.

Observability

Monitoring

Track your Apache Druid ⇄ Outreach 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 Outreach.

How the Apache Druid and Outreach 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

Outreach

Integration surface
REST API conforming to the JSON:API specification
Authentication
OAuth 2.0
Change detection
webhook subscriptions on resource create, update, and destroy events, plus polling
Capabilities
read · write · webhooks
Rate limits
subject to per-user hourly rate limits
How it works

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

    Choose tables

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

Apache Druid and Outreach 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 433 integrations available for Apache Druid and Outreach.

Popular · 8 of 433
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