Two-way sync
Changes in BigQuery or Kustomer instantly reflect in both systems. No stale data, no manual imports.
Keep BigQuery and Kustomer in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.
Stacksync does both with one connection. Customers, Conversations, Messages, Companies from Kustomer land in BigQuery as live tables, updated within seconds, and columns computed in BigQuery write back to fields in Kustomer. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Deduplication and normalization done in BigQuery can be written back, so warehouse-side cleanup actually fixes the CRM.
Accounts, contacts, and activity from Kustomer are queryable in BigQuery moments after they change, so dashboards stop lagging the reality they describe.
Lead scores, churn risk, or usage segments computed in BigQuery appear as fields in Kustomer, where the people working accounts actually see them.
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.
| BigQuery objects | Kustomer objects | |
|---|---|---|
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | Messages Individual messages within conversations support full-thread replication. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Companies Organization records group customers and map to CRM accounts. | |
| Clustered tables Supported; clustering is transparent to the sync. | Custom Objects (Klasses) Structured external records such as orders and subscriptions synced in to appear on the customer timeline. | |
| Datasets Organizational container — you pick which dataset’s tables to sync. | Users Agent records map conversation ownership to people in other systems. | |
| Projects Connection scope: the service account grants access per project. | Teams Team assignments support routing parity and reporting. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–Kustomer connection.
Changes in BigQuery or Kustomer instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever BigQuery or Kustomer data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single BigQuery or Kustomer record.
Track your BigQuery ⇄ Kustomer sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between BigQuery and Kustomer.
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 BigQuery and Kustomer 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 BigQuery and Kustomer 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 BigQuery and Kustomer: authenticate both systems, choose the objects to sync (such as BigQuery's Tables and Partitioned tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both BigQuery and Kustomer. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on BigQuery: Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in. On Kustomer: Outbound webhooks on record 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 Kustomer side: Customers, Conversations, Messages, Companies, plus custom fields where Kustomer exposes them. On the BigQuery side: Clustered tables, Datasets, Projects, 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 BigQuery and Kustomer: Cleanup that sticks; CRM analytics on live data; Scores and segments back on the record. Deduplication and normalization done in BigQuery can be written back, so warehouse-side cleanup actually fixes the CRM.
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 386 integrations available for BigQuery and Kustomer.