Real-time sync
Changes in Apache Kylin or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
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.
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.
Point analytical queries at the synced copy in Apache Kylin and keep PostgreSQL focused on its operational workload.
Rows from PostgreSQL land in Apache Kylin as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Apache Kylin sync into PostgreSQL, where whatever reads from that database gets them without querying the warehouse.
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 | |
|---|---|---|
| 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. | |
| Segments Time-ranged build units that partition pre-computed data. | Materialized Views Precomputed result sets synced outward on a refresh schedule. | |
| 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. | |
| 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. | |
| 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. | |
| 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. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Kylin–PostgreSQL connection.
Changes in Apache Kylin or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Kylin or PostgreSQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Kylin or PostgreSQL record.
Track your Apache Kylin ⇄ PostgreSQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Kylin and PostgreSQL.
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.
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.
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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time integration between Apache Kylin and PostgreSQL — Apache Kylin is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
Change detection on Apache Kylin: Not applicable for row-level capture; data freshness follows segment build and refresh jobs, so integrations poll query results. On PostgreSQL: 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. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Kylin side: Segments, Build Jobs, Projects, Models, plus custom fields where Apache Kylin exposes them. On the PostgreSQL side: JSONB Columns, Sequences, Custom Types and Enums, Tables. Stacksync auto-detects both schemas and converts types between the two systems.
Apache Kylin is a read-only source, so this integration runs one-way: Stacksync reads from Apache Kylin in real time and delivers into PostgreSQL. Field mapping and monitoring work the same as for two-way pairs.
Common patterns for Apache Kylin and PostgreSQL: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Apache Kylin and keep PostgreSQL focused on its operational workload.
Apache Kylin: SQL over JDBC/ODBC plus a REST API for queries and administration. Authentication: Username/password (HTTP basic authentication on the REST API). PostgreSQL: 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. Stacksync manages authentication, retries, and rate limits on both sides.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Kylin and PostgreSQL.