Two-way sync
Changes in Airtable or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Keep Airtable and Google Cloud Platform in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Airtable's rows in Google Cloud Platform, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Airtable where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Airtable sync into Google Cloud Platform in real time, and result tables in Google Cloud Platform sync back into Airtable, with schema and type mapping between the two systems handled for you.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Google Cloud Platform and keep Airtable focused on its operational workload.
Rows from Airtable land in Google Cloud Platform as they change, replacing hand-built CDC and batch extract jobs.
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.
| Airtable objects | Google Cloud Platform objects | |
|---|---|---|
| Linked records Cross-table references that carry relationships between synced tables. | Pub/Sub topics Event streams used to move change events between systems in near real time. | |
| Attachments File fields exposed as expiring URLs that syncs can mirror to other systems. | Firestore documents Document data read and written through the Firestore API for app-facing syncs. | |
| Collaborators User fields useful for mapping record ownership to accounts in a CRM or database. | Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. | |
| Bases Top-level containers; each base has its own API endpoint and schema. | BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. | |
| Tables Map to sync tables; schema is readable through the base metadata endpoints. | BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. | |
| Records The row-level unit created, updated, and deleted during syncs, identified by rec-prefixed IDs. | Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Airtable–Google Cloud Platform connection.
Changes in Airtable or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Airtable or Google Cloud Platform data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Airtable or Google Cloud Platform record.
Track your Airtable ⇄ Google Cloud Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Airtable and Google Cloud Platform.
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 Airtable and Google Cloud Platform 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 Airtable and Google Cloud Platform 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 Airtable and Google Cloud Platform: authenticate both systems, choose the objects to sync (such as Airtable's Linked records and Attachments), map fields visually, and changes propagate both ways in milliseconds — no code required.
Google Cloud Platform: BigQuery is append-oriented: row mutations go through DML or the Storage Write API, and streamed rows pass through a buffer before some operations can touch them. Airtable: Computed field types such as formulas, lookups, and rollups are read-only over the API, so bi-directional syncs must map writes to source fields. Stacksync's field mapping accounts for these differences between Airtable and Google Cloud Platform 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 Airtable and Google Cloud Platform records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Airtable and Google Cloud Platform connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Airtable–Google Cloud Platform integration in-house.
Yes — Stacksync ships production-grade connectors for both Airtable and Google Cloud Platform. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Airtable: Incremental updates: changes in Airtable are detected and synced efficiently in realtime (webhook-based — creator role required to create webhooks); formula fields don't emit change events and are re-synced every hour. On Google Cloud Platform: Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery tables. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 Airtable and Google Cloud Platform.