The Challenge
Multi-tenant SaaS platforms need data isolation—each customer’s data lives in its own environment for security, compliance, and performance reasons. But managing this at scale creates significant operational overhead:
- New customer onboarding requires manual BigQuery dataset and table creation, delaying time-to-value
- Schema updates must be applied consistently across dozens or hundreds of tenant environments—a manual nightmare
- Offboarding customers requires systematic dataset cleanup; leaving orphaned data creates compliance and cost risks
- Inconsistencies creep in when engineers handle provisioning manually, causing support issues unique to specific tenants
- As customer count grows, the operational burden scales linearly—unless the process is automated
Engineering teams end up spending significant time on infrastructure management that should be handled systematically.
The Autohive Solution
Autohive’s Google BigQuery integration enables platform teams to build automated workflows that manage the entire tenant data lifecycle—from first login to final deletion—without manual intervention.
Automated Tenant Provisioning
When a new customer signs up, Autohive agents automatically create a dedicated BigQuery dataset for their environment and initialise the required table structure. Customers are ready to use data features from day one.
Schema Evolution Management
When you update your data model, Autohive agents iterate through all tenant datasets and apply schema changes consistently. Whether you’re adding columns, creating new tables, or modifying existing structures, every tenant environment stays in sync.
Controlled Tenant Offboarding
When a customer leaves, Autohive orchestrates the complete data removal workflow—deleting tables, removing datasets, and confirming cleanup—ensuring no orphaned data remains in your warehouse.
Project-wide Visibility
List all datasets across your BigQuery projects to audit tenant environments, identify inactive datasets, and ensure your warehouse reflects your actual customer base at any point in time.
Benefits
- Instant customer onboarding – Data environments provisioned automatically at signup, not hours later
- Consistent schema across tenants – Schema updates applied uniformly without manual coordination
- Reduced engineering overhead – Platform teams focus on features, not infrastructure operations
- Clean offboarding – Complete, auditable data removal for compliance and cost management
- Scales with your customer base – 10 tenants or 10,000 tenants, the same automated workflow handles both
How It Works
- Design your tenant data structure – Define the dataset naming convention and table schema for each customer environment
- Trigger on customer events – Connect Autohive to your CRM or user management system to fire provisioning on new signups and deprovisioning on cancellations
- Create datasets and tables – The agent calls BigQuery’s dataset and table creation actions with tenant-specific naming and your standard schema
- Manage schema updates – When data model changes are needed, the agent lists all tenant datasets and applies the update to each one systematically
- Handle offboarding – On cancellation, the agent deletes all tables and the dataset, confirming complete removal
- Audit regularly – Periodic listing of all datasets against your active customer list catches any discrepancies
Getting Started
- Sign up at app.autohive.com
- Connect the Google BigQuery integration from the Autohive marketplace
- Define your tenant dataset and table templates
- Connect your customer lifecycle events (signup, cancellation) to trigger provisioning workflows
- Deploy and watch tenant environments appear automatically
