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Business productivity ⇄ Data warehouse

Aviato to BigQuery integration — real-time data sync

Keep Aviato and BigQuery 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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Why teams connect Aviato and BigQuery

Get the data locked inside Aviato into BigQuery as live tables, and send results back where Aviato can use them, without writing a pipeline.

Aviato is a read-only source: Stacksync reads its data in real time and delivers it into BigQuery, so BigQuery always reflects the current state of Aviato — without exports, scripts, or schedulers.

Whatever Aviato is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.

Common use cases

  • Keep a warehouse table of tracked private companies refreshed on a schedule for downstream scoring and reporting
  • Pull founder and team data into a sourcing database to flag new startups that match an investment thesis
  • Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs

History that outlives the tool

A continuously synced copy in BigQuery preserves a queryable record even as data ages out of Aviato or gets changed inside it.

Analytics on Aviato's data

Records and events from Aviato land in BigQuery as queryable tables, current within seconds and ready to join with the rest of the warehouse.

Cross-tool reporting

Combine Aviato's data with data from every other synced system to answer questions no single tool can.

What you can sync between Aviato and BigQuery

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.

Aviato objects BigQuery objects
Person Founder and employee profiles linked to current and past companies Tables The syncable unit: only tables can be synced per the Stacksync docs.
Funding Round Round-level records with stage, amount, date, and participating investors Partitioned tables Synced like regular tables; partition columns map to target fields.
Investor Funds and angels connected to the rounds and companies they back Clustered tables Supported; clustering is transparent to the sync.
Headcount Snapshot Point-in-time employee counts used to track company growth over time Datasets Organizational container — you pick which dataset’s tables to sync.
Employment Record Person-to-company links with role and tenure that model team movement Projects Connection scope: the service account grants access per project.
What ships with Aviato ⇄ BigQuery

Connect Aviato and BigQuery for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Aviato–BigQuery connection.

Real-time

Real-time sync

Changes in Aviato or BigQuery instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Aviato or BigQuery 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 Aviato or BigQuery record.

Observability

Monitoring

Track your Aviato ⇄ BigQuery sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Aviato and BigQuery.

How the Aviato and BigQuery connectors work

Aviato

Integration surface
REST API returning JSON, with search/filter endpoints for querying company and people records
Authentication
API key passed on each request
Change detection
Polling-based: re-query tracked records on a schedule and diff against the last synced state; no native change feed is assumed
Capabilities
read
Rate limits
Request volume is credit- and rate-limited per plan; schedule refreshes in batches rather than per-record calls

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
BigQuery setup guide
How it works

How to connect Aviato to BigQuery — 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.

  1. 01

    Connect your apps

    Authenticate Aviato and BigQuery with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Aviato connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Aviato and BigQuery 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Aviato ⇄ BigQuery
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Aviato BigQuery
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Aviato and BigQuery integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Aviato and BigQuery.

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