Two-way sync
Changes in Citus or ServiceNow instantly reflect in both systems. No stale data, no manual imports.
Keep Citus and ServiceNow in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Engineers integrate with tools like ServiceNow through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Citus.
Stacksync mirrors Knowledge Articles, Custom Tables, Incidents, Change Requests from ServiceNow into Schemas, Views, Sequences, Distributed tables in Citus and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into ServiceNow, so the tool and the database never disagree.
Write to the synced tables in Citus and Stacksync propagates the change into ServiceNow, replacing custom integration code.
Updates in ServiceNow arrive as row changes in Citus, so triggers, jobs, and services can respond in near real time.
Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.
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 | ServiceNow objects | How this pairing syncs | |
|---|---|---|---|
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Service Catalog Requests Requested items and approvals that often trigger provisioning in other systems. | Distributed tables is specific to Citus and Service Catalog Requests to ServiceNow — 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. | Configuration Items (CMDB) Asset and infrastructure records synced with discovery tools and asset databases. | Reference tables is specific to Citus and Configuration Items (CMDB) to ServiceNow — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Users and Groups Sys_user and group tables synced with HR systems and identity providers. | Local tables is specific to Citus and Users and Groups to ServiceNow — 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. | Tasks The base task table that incidents, changes, and requests extend. | Schemas is specific to Citus and Tasks to ServiceNow — 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. | Knowledge Articles Support content that can be mirrored to help centers or search indexes. | Views is specific to Citus and Knowledge Articles to ServiceNow — 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. | Custom Tables Scoped or u_-prefixed tables are addressable through the same Table API as standard ones. | Sequences is specific to Citus and Custom Tables to ServiceNow — 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 ServiceNow through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls ServiceNow for changes on an incremental schedule, reading only records changed since the previous pass. Polling on sys_updated_on timestamps.
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–ServiceNow connection.
Changes in Citus or ServiceNow instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Citus or ServiceNow 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 ServiceNow record.
Track your Citus ⇄ ServiceNow sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Citus and ServiceNow.
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 ServiceNow 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 ServiceNow 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 ServiceNow: 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.
Yes — Stacksync ships production-grade connectors for both Citus and ServiceNow. 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 ServiceNow: Polling on sys_updated_on timestamps; instance admins can configure outbound push through business rules or Flow Designer. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the ServiceNow side: Knowledge Articles, Custom Tables, Incidents, Change Requests, plus custom fields where ServiceNow exposes them. On the Citus side: Schemas, Views, Sequences, Distributed tables. 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.
Common patterns for Citus and ServiceNow: Automate ServiceNow from your codebase; React to changes as they happen; One integration pattern for the whole stack. Write to the synced tables in Citus and Stacksync propagates the change into ServiceNow, replacing custom integration code.
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 411 integrations available for Citus and ServiceNow.