Two-way sync
Changes in Citus or Gainsight instantly reflect in both systems. No stale data, no manual imports.
Keep Citus and Gainsight 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 Gainsight 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 Company, Person (People), Relationship, CTA (Call to Action) from Gainsight 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 Gainsight, so the tool and the database never disagree.
Write to the synced tables in Citus and Stacksync propagates the change into Gainsight, replacing custom integration code.
Updates in Gainsight 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 | Gainsight objects | How this pairing syncs | |
|---|---|---|---|
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | CTA (Call to Action) Risk and expansion alerts that drive CSM plays; often synced to ticketing or project tools so follow-up work is tracked where teams operate. | Distributed tables is specific to Citus and CTA (Call to Action) to Gainsight — 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. | Scorecard Fact Health scores and measures per Company or Relationship; usage metrics from a warehouse are written in so scores reflect live telemetry. | Reference tables is specific to Citus and Scorecard Fact to Gainsight — each maps to any object or custom field on the other side. | |
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Timeline Activity Logged calls, emails, and notes; usually read out into a reporting database for QBR and churn analysis. | Local tables is specific to Citus and Timeline Activity to Gainsight — 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. | Success Plan Account objectives with associated tasks; read out for reporting or synced with project tools tracking onboarding and adoption. | Schemas is specific to Citus and Success Plan to Gainsight — 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. | Task and Playbook Cockpit tasks generated from CTAs and playbooks; synced with Jira or Asana so execution happens in the team's own tool. | Views is specific to Citus and Task and Playbook to Gainsight — 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 Objects Org-specific MDA tables with the __gc suffix; discoverable via the Describe API so field mappings can be generated automatically. | Sequences is specific to Citus and Custom Objects to Gainsight — 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 Gainsight through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls Gainsight for changes on an incremental schedule, reading only records changed since the previous pass. Polling on the ModifiedDate (GS Modified Date) system field, which is filterable and sortable on every object.
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–Gainsight connection.
Changes in Citus or Gainsight instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Citus or Gainsight 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 Gainsight record.
Track your Citus ⇄ Gainsight sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Citus and Gainsight.
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 Gainsight 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 Gainsight 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 Gainsight: 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.
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 Gainsight: Polling on the ModifiedDate (GS Modified Date) system field, which is filterable and sortable on every object; Rules Engine Real-Time Rules can optionally push specific object events (e.g., a Company stage change) to an external endpoint. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Gainsight side: Company, Person (People), Relationship, CTA (Call to Action), plus custom fields where Gainsight 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 Gainsight: Automate Gainsight 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 Gainsight, replacing custom integration code.
Citus: PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node. Authentication: Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options). Gainsight: REST APIs (per-object) and asynchronous Bulk REST API. Authentication: API access key passed in the 'accesskey' request header (non-expiring), generated by a Gainsight admin; M2M OAuth (Client ID/Secret) is also supported. 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 437 integrations available for Citus and Gainsight.