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Data warehouse

Apache Druid to Apache Kylin integration — real-time data sync

Keep Apache Druid and Apache Kylin 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

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Migrated from Mulesoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Apache Druid and Apache Kylin

Keep tables consistent across Apache Druid and Apache Kylin, for a migration, a multi-warehouse stack, or a dataset two platforms both need.

Apache Kylin 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 Apache Kylin — without exports, scripts, or schedulers.

Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.

Common use cases

  • Query aggregated event metrics from Druid and sync them into CRM account fields for usage-based selling.
  • Feed operational records into Druid via batch ingestion so analysts get interactive slice-and-dice on fresh data.
  • Trigger downstream syncs after segment build jobs complete so consumers only read refreshed data.
  • Read pre-aggregated metrics from Kylin and sync them into CRM fields or planning spreadsheets on a schedule.

Shared datasets across teams

Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.

Consolidation after M&A

Bring the acquired company's warehouse data across continuously instead of through one-off dumps.

Migration without a big bang

When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.

What you can sync between Apache Druid and Apache Kylin

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 Apache Kylin objects
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Cubes / Indexes Pre-computed aggregate structures that answer queries at low latency.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Source Tables Hive or other upstream tables that builds read from.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Segments Time-ranged build units that partition pre-computed data.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Build Jobs Batch jobs that compute or refresh segments, monitored via the REST API.
Lookups Key-value mappings joined at query time, refreshable from external systems. Projects Top-level workspaces that group models, tables, and jobs.
Tasks Batch ingestion and compaction jobs monitored during data loads. Models Star-schema definitions over source tables that determine what can be queried.
What ships with Apache Druid ⇄ Apache Kylin

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

Track your Apache Druid ⇄ Apache Kylin 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 Apache Kylin.

How the Apache Druid and Apache Kylin 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

Apache Kylin

Integration surface
SQL over JDBC/ODBC plus a REST API for queries and administration
Authentication
Username/password (HTTP basic authentication on the REST API)
Change detection
Not applicable for row-level capture; data freshness follows segment build and refresh jobs, so integrations poll query results
Capabilities
read
Rate limits
No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage
How it works

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

    Choose tables

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

Apache Druid and Apache Kylin integration FAQ

SECURITY

Security teams love 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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→ 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 386 integrations available for Apache Druid and Apache Kylin.

Popular · 8 of 386
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