Two-way sync
Changes in BigQuery or Nutshell instantly reflect in both systems. No stale data, no manual imports.
Keep BigQuery and Nutshell 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. Products, Tags, Users, Leads from Nutshell land in BigQuery as live tables, updated within seconds, and columns computed in BigQuery write back to fields in Nutshell. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Join Nutshell's relationship data with billing, product, and support data in BigQuery to build the customer picture the CRM alone cannot hold.
Deduplication and normalization done in BigQuery can be written back, so warehouse-side cleanup actually fixes the CRM.
Accounts, contacts, and activity from Nutshell are queryable in BigQuery moments after they change, so dashboards stop lagging the reality they describe.
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 | Nutshell objects | How this pairing syncs | |
|---|---|---|---|
| Projects Connection scope: the service account grants access per project. | People Individual contacts, kept consistent with marketing and outreach tools | Projects is specific to BigQuery and People to Nutshell — each maps to any object or custom field on the other side. | |
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | Companies Account records that group people and leads for account-level syncs | Tables is specific to BigQuery and Companies to Nutshell — each maps to any object or custom field on the other side. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Activities Logged calls, meetings, and emails used for engagement reporting | Partitioned tables is specific to BigQuery and Activities to Nutshell — each maps to any object or custom field on the other side. | |
| Clustered tables Supported; clustering is transparent to the sync. | Tasks Rep to-dos mirrored into external work-management or reporting systems | Clustered tables is specific to BigQuery and Tasks to Nutshell — each maps to any object or custom field on the other side. | |
| Datasets Organizational container — you pick which dataset’s tables to sync. | Notes Free-text history attached to leads and contacts, replicated for a full timeline | Datasets is specific to BigQuery and Notes to Nutshell — 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 BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").
DeliveryEach detected change is written to Nutshell through its API, with automatic retries and rate-limit backoff.
DetectionNutshell notifies Stacksync of record changes through webhook events. Webhook subscriptions for record events, with polling as fallback.
DeliveryEach detected change is applied to BigQuery as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–Nutshell connection.
Changes in BigQuery or Nutshell instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever BigQuery or Nutshell 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 Nutshell record.
Track your BigQuery ⇄ Nutshell sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between BigQuery and Nutshell.
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 Nutshell 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 Nutshell 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 Nutshell: authenticate both systems, choose the objects to sync (such as BigQuery's Projects and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
BigQuery: GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs. Authentication: Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver. Nutshell: JSON-RPC API over HTTPS; a newer REST API is also offered. Authentication: HTTP Basic with account email and API key. Stacksync manages authentication, retries, and rate limits on both sides.
Nutshell: Nutshell's most full-featured API is JSON-RPC: each call names a method such as findLeads or editLead instead of hitting resource URLs, though a newer REST API is also available. BigQuery: The Storage Write API supports high-throughput streaming ingestion, which suits continuous sync loads better than legacy streaming inserts. Stacksync's field mapping accounts for these differences between BigQuery and Nutshell without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means BigQuery and Nutshell records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed BigQuery and Nutshell connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom BigQuery–Nutshell integration in-house.
Yes — Stacksync ships production-grade connectors for both BigQuery and Nutshell. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 456 integrations available for BigQuery and Nutshell.