Real-time sync
Changes in Apache Kylin or Greenplum instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Kylin and Greenplum 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 Greenplum, so Greenplum 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.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
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 | Greenplum objects | How this pairing syncs | |
|---|---|---|---|
| Models Star-schema definitions over source tables that determine what can be queried. | Views Read-only projections used to shape data before syncing it out. | Models is specific to Apache Kylin and Views to Greenplum — each maps to any object or custom field on the other side. | |
| Cubes / Indexes Pre-computed aggregate structures that answer queries at low latency. | External tables Reference external files for bulk load paths alongside row-level syncs. | Cubes / Indexes is specific to Apache Kylin and External tables to Greenplum — each maps to any object or custom field on the other side. | |
| Source Tables Hive or other upstream tables that builds read from. | Rows Read and written by key; distribution keys determine where rows live. | Source Tables is specific to Apache Kylin and Rows to Greenplum — each maps to any object or custom field on the other side. | |
| Segments Time-ranged build units that partition pre-computed data. | Databases Top-level containers that scope a sync connection. | Segments is specific to Apache Kylin and Databases to Greenplum — 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 Namespace tables and control which objects a sync can see. | Build Jobs is specific to Apache Kylin and Schemas to Greenplum — each maps to any object or custom field on the other side. | |
| Projects Top-level workspaces that group models, tables, and jobs. | Tables Heap or append-optimized tables mapped directly to sync targets. | Projects is specific to Apache Kylin and Tables to Greenplum — each maps to any object or custom field on the other side. |
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.
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 Greenplum as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Greenplum for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key-based cursors.
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 Greenplum records.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Kylin–Greenplum connection.
Changes in Apache Kylin or Greenplum instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Kylin or Greenplum 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 Greenplum record.
Track your Apache Kylin ⇄ Greenplum sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Kylin and Greenplum.
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 Greenplum 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 Greenplum 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 Greenplum — 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.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Kylin and Greenplum connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Kylin–Greenplum integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Kylin and Greenplum. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 Greenplum: Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC. 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: Models, Cubes / Indexes, Source Tables, Segments, plus custom fields where Apache Kylin exposes them. On the Greenplum side: Partitions, Views, External tables, Rows. 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 Greenplum. Field mapping and monitoring work the same as for two-way pairs.
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 326 integrations available for Apache Kylin and Greenplum.