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Data warehouse ⇄ Database

Apache Kylin to PostgreSQL integration — real-time data sync

Keep Apache Kylin and PostgreSQL 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 Kylin and PostgreSQL

Flow Apache Kylin data into PostgreSQL in real time — no exports, no schedulers, no custom scripts.

Apache Kylin is a read-only source: Stacksync reads its data in real time and delivers it into PostgreSQL, so PostgreSQL always reflects the current state of Apache Kylin — without exports, scripts, or schedulers.

Operational databases and analytical warehouses want the same data at different moments. Analysts want PostgreSQL's rows in Apache Kylin, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in PostgreSQL where the services that read from it get them at normal query latency.

Common use cases

  • 01 Sync Kylin aggregates into a cloud warehouse to combine them with data Kylin does not cover.
  • 02 Trigger downstream syncs after segment build jobs complete so consumers only read refreshed data.
  • 03 Feed reporting and BI from a continuously synced Postgres replica instead of scheduled ETL scripts
  • 04 Expose SaaS objects (CRM contacts, ERP invoices, support tickets) as Postgres tables that internal tools can query and join

Common sync patterns

Offload heavy reads

Point analytical queries at the synced copy in Apache Kylin and keep PostgreSQL focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from PostgreSQL land in Apache Kylin as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Apache Kylin sync into PostgreSQL, where whatever reads from that database gets them without querying the warehouse.

What you can sync between Apache Kylin and PostgreSQL

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 Kylin objects PostgreSQL objects How this pairing syncs
Source Tables Hive or other upstream tables that builds read from. Views Read-side projections used to expose joined or filtered data to a sync. Source Tables is specific to Apache Kylin and Views to PostgreSQL — each maps to any object or custom field on the other side.
Segments Time-ranged build units that partition pre-computed data. Materialized Views Precomputed result sets synced outward on a refresh schedule. Segments is specific to Apache Kylin and Materialized Views to PostgreSQL — each maps to any object or custom field on the other side.
Build Jobs Batch jobs that compute or refresh segments, monitored via the REST API. Schemas Namespaces that scope which tables a sync reads and writes. Build Jobs is specific to Apache Kylin and Schemas to PostgreSQL — each maps to any object or custom field on the other side.
Projects Top-level workspaces that group models, tables, and jobs. Columns Field-level mapping targets; types are mapped to the connected system's field types. Projects is specific to Apache Kylin and Columns to PostgreSQL — each maps to any object or custom field on the other side.
Models Star-schema definitions over source tables that determine what can be queried. Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. Models is specific to Apache Kylin and Primary and Unique Keys to PostgreSQL — each maps to any object or custom field on the other side.
Cubes / Indexes Pre-computed aggregate structures that answer queries at low latency. JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. Cubes / Indexes is specific to Apache Kylin and JSONB Columns to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between Apache Kylin and PostgreSQL

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 Kylin PostgreSQL Interval-based propagation

DetectionStacksync polls Apache Kylin for changes on an incremental schedule, reading only records changed since the previous pass. Data freshness follows segment build and refresh jobs, so integrations poll query results.

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

PostgreSQL Apache Kylin Sub-second propagation

DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.

DeliveryApache Kylin does not accept inbound record writes, so this direction carries requests rather than records: Apache Kylin's output flows back as field updates on the originating PostgreSQL records.

Rate-limit considerations

  • Apache Kylin: No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage.
  • PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
What ships with Apache Kylin ⇄ PostgreSQL

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Kylin and PostgreSQL.

How the Apache Kylin and PostgreSQL connectors work

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

PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL frontend/backend protocol)
Authentication
Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
Change detection
Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
PostgreSQL setup guide
How it works

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

    Choose tables

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

Apache Kylin and PostgreSQL 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 431 integrations available for Apache Kylin and PostgreSQL.

Popular · 4 of 431
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