Real-time
Two-way sync
Changes in BigQuery or Sage 300 instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ ERP
BigQuery to Sage 300 integration — real-time, two-way sync
Keep BigQuery and Sage 300 in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from Mulesoft
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Migrated from Celigo
Why teams connect BigQuery and Sage 300
Put Sage 300's records in BigQuery as live tables for reporting and analysis, without extract jobs, and write results back where Sage 300 can use them.
ERP data is some of the most asked-for data in the warehouse and some of the hardest to get: the record types are many, the APIs are strict, and extract jobs are brittle. Whether Sage 300 carries financials, operations, workforce data, or all three, the analysis belongs in BigQuery next to everything else the company measures.
Stacksync syncs AR Invoices and Receipts, AR Customers, AP Vendors, GL Accounts from Sage 300 into tables in BigQuery continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in BigQuery can be written back to fields in Sage 300 where that is useful.
Common use cases
- Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
- Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
- Replicate GL, AR, and AP detail to a warehouse for consolidated multi-company reporting.
- Keep inventory items and quantities aligned with e-commerce and warehouse systems on a schedule.
Where Sage 300 runs operations: order and supply analysis
Operational records become queryable tables in BigQuery, joinable with sales and finance data.
Group reporting across systems
Combine Sage 300's records with data synced from other systems in BigQuery for consolidated views no single system can produce.
Write-back where Sage 300 exposes writable fields
Classifications or reference values computed in BigQuery sync back onto the corresponding records in Sage 300.
What you can sync between BigQuery and Sage 300
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 | Sage 300 objects | |
|---|---|---|
| Datasets Organizational container — you pick which dataset’s tables to sync. | Journal Batches GL entries staged in batches that must be posted; a common write target for external systems. | |
| Projects Connection scope: the service account grants access per project. | Order Entry Orders Sales orders written from e-commerce or EDI feeds. | |
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | Purchase Orders Procurement documents read for spend visibility and receiving. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Inventory Items Item master with costing and quantities, synced to storefronts and WMS. | |
| Clustered tables Supported; clustering is transparent to the sync. | AR Invoices and Receipts Billing and payment records replicated for cash and revenue reporting. |
What ships with BigQuery ⇄ Sage 300
Connect BigQuery and Sage 300 for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–Sage 300 connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever BigQuery or Sage 300 data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single BigQuery or Sage 300 record.
Observability
Monitoring
Track your BigQuery ⇄ Sage 300 sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between BigQuery and Sage 300.
How the BigQuery and Sage 300 connectors work
BigQuery
- Integration surface
- 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
- Change detection
- 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
- Capabilities
- read · write · CDC
- Rate limits
- Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
Sage 300
- Integration surface
- Sage 300 Web API (REST) on newer releases; .NET/COM SDK and direct SQL Server access on-prem
- Authentication
- Sage 300 user credentials (Basic auth on the Web API); database credentials for direct SQL reads
- Change detection
- Scheduled polling; batch-oriented modules with no webhook surface
- Capabilities
- read · write
How it works
How to connect BigQuery to Sage 300 — three steps, no code
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.
- 01
Connect your apps
Authenticate BigQuery and Sage 300 with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
BigQuery
connected
Sage 300
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the BigQuery and Sage 300 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.
objects · BigQuery ⇄ Sage 300Customers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
BigQuery Sage 300Company company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
BigQuery and Sage 300 integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between BigQuery and Sage 300: authenticate both systems, choose the objects to sync (such as BigQuery's Datasets and Projects), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the BigQuery side: Clustered tables, Datasets, Projects, Tables, plus custom fields where BigQuery exposes them. On the Sage 300 side: AR Invoices and Receipts, AR Customers, AP Vendors, GL Accounts. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
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Common patterns for BigQuery and Sage 300: Where Sage 300 runs operations: order and supply analysis; Group reporting across systems; Write-back where Sage 300 exposes writable fields. Operational records become queryable tables in BigQuery, joinable with sales and finance data.
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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. Sage 300: Sage 300 Web API (REST) on newer releases; .NET/COM SDK and direct SQL Server access on-prem. Authentication: Sage 300 user credentials (Basic auth on the Web API); database credentials for direct SQL reads. Stacksync manages authentication, retries, and rate limits on both sides.
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BigQuery: Views and materialized views are not supported — only tables. Sage 300: Sage 300 (formerly Accpac) stores each company's data in its own SQL Server database with module-prefixed tables, so direct SQL reads are a common integration path on-prem. Stacksync's field mapping accounts for these differences between BigQuery and Sage 300 without custom code.
SECURITY
Security teams love Stacksync
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.
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for BigQuery and Sage 300.
Popular · 8 of 386
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BigQuery ⇄ NetSuite -
BigQuery ⇄ Dynamics 365 F&O - BigQuery ⇄ SuiteAnalytics
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BigQuery ⇄ Dynamics 365 Business Central -
Sage 300 ⇄ Dremio -
Sage 300 ⇄ Exasol -
Sage 300 ⇄ Firebolt -
Sage 300 ⇄ Google Cloud Platform
No integrations match .
