Two-way sync
Changes in Citus or Intercom instantly reflect in both systems. No stale data, no manual imports.
Keep Citus and Intercom in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in Citus, where it can be queried and joined like everything else.
Stacksync mirrors Companies, Conversations, Tickets, Data Events from Intercom into Schemas, Views, Sequences, Distributed tables in Citus with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Intercom with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.
Field and stage updates in Intercom arrive as row changes in Citus, ready to drive jobs and notifications.
Accounts, contacts, and custom objects from Intercom become tables in Citus you can join with application data directly.
Signup, usage, or lifecycle changes written to Citus sync onto the matching records in Intercom, giving go-to-market teams live product context.
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 | Intercom objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Tickets Structured ticket records track issues alongside conversational threads. | Schemas is specific to Citus and Tickets to Intercom — 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. | Data Events Behavioral events pushed in from product databases trigger messages and flows. | Views is specific to Citus and Data Events to Intercom — 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 Data Attributes Typed custom fields on contacts and companies hold synced billing and usage data. | Sequences is specific to Citus and Custom Data Attributes to Intercom — each maps to any object or custom field on the other side. | |
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Tags Labels applied to contacts, companies, and conversations sync for routing and reporting. | Distributed tables is specific to Citus and Tags to Intercom — 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. | Segments Saved audience definitions are readable for targeting parity across tools. | Reference tables is specific to Citus and Segments to Intercom — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Admins & Teams Teammate records map conversation ownership to CRM users. | Local tables is specific to Citus and Admins & Teams to Intercom — 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 Intercom through its API, with automatic retries and rate-limit backoff.
DetectionIntercom notifies Stacksync of record changes through webhook events. Webhook topic subscriptions for contact, company, and conversation events, plus polling for backfill.
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–Intercom connection.
Changes in Citus or Intercom instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Citus or Intercom 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 Intercom record.
Track your Citus ⇄ Intercom sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Citus and Intercom.
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 Intercom 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 Intercom 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 Intercom: authenticate both systems, choose the objects to sync (such as Citus's Schemas and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Citus and Intercom. 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 Intercom: Webhook topic subscriptions for contact, company, and conversation events, plus polling for backfill. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Intercom side: Companies, Conversations, Tickets, Data Events, plus custom fields where Intercom 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 Intercom: Trigger workflows from CRM changes; Query the CRM like a database; Product events onto CRM records. Field and stage updates in Intercom arrive as row changes in Citus, ready to drive jobs and notifications.
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 439 integrations available for Citus and Intercom.