Two-way sync
Changes in Citus or Infor LN instantly reflect in both systems. No stale data, no manual imports.
Keep Citus and Infor LN in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
ERP data sits behind interfaces built for the ERP's own modules, not for your internal systems. Teams that need those records, for reporting services, internal tools, or automations, end up writing integration code against a strict API and maintaining it through every upgrade.
Stacksync mirrors Warehouse / inventory, Projects, Service orders, Items from Infor LN into Citus and keeps both sides consistent in real time. Whatever Infor LN is the system of record for, whether financials, operations, people, or procurement, those records become rows your code can query, and changes written in Citus sync back into Infor LN with its validations respected.
Records from Infor LN live in Citus as ordinary tables or collections, joinable with the rest of your data.
Scripts and services read and write the synced tables; Stacksync handles the Infor LN interface, limits, and retries.
Updates in Infor LN arrive as row changes in Citus, so jobs and triggers can respond as the business record changes.
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.
| Citus objects | Infor LN objects | How this pairing syncs | |
|---|---|---|---|
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Warehouse / inventory Stock positions exposed so external channels reflect real availability. | Distributed tables is specific to Citus and Warehouse / inventory to Infor LN — each maps to any object or custom field on the other side. | |
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Projects Project structures used in engineer-to-order manufacturing scenarios. | Reference tables is specific to Citus and Projects to Infor LN — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Service orders Aftermarket service documents synced with field service tools. | Local tables is specific to Citus and Service orders to Infor LN — each maps to any object or custom field on the other side. | |
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Items Manufacturing item masters synced to PLM, MES, and commerce systems. | Schemas is specific to Citus and Items to Infor LN — each maps to any object or custom field on the other side. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | Bills of material Product structures shared with engineering and planning tools. | Views is specific to Citus and Bills of material to Infor LN — each maps to any object or custom field on the other side. | |
| Sequences Key generators that matter when external writes must not collide with application inserts. | Business partners LN's unified customer/supplier records matched against CRM accounts. | Sequences is specific to Citus and Business partners to Infor LN — 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.
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
DeliveryEach detected change is written to Infor LN through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls Infor LN for changes on an incremental schedule, reading only records changed since the previous pass. Event-style BOD publications through Infor ION where configured.
DeliveryEach detected change is applied to Citus as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Infor LN connection.
Changes in Citus or Infor LN instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Citus or Infor LN data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Citus or Infor LN record.
Track your Citus ⇄ Infor LN sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Citus and Infor LN.
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 Citus and Infor LN 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 Citus and Infor LN 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 two-way integration between Citus and Infor LN: authenticate both systems, choose the objects to sync (such as Citus's Distributed tables and Reference tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Citus and Infor LN connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Citus–Infor LN integration in-house.
Yes — Stacksync ships production-grade connectors for both Citus and Infor LN. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Citus: PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres. On Infor LN: Event-style BOD publications through Infor ION where configured; otherwise polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Citus side: Reference tables, Local tables, Schemas, Views, plus custom fields where Citus exposes them. On the Infor LN side: Warehouse / inventory, Projects, Service orders, Items. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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.
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Every pair below is a real-time, two-way sync. Search all 431 integrations available for Citus and Infor LN.