Two-way sync
Changes in Google Cloud Platform or Google Cloud Spanner instantly reflect in both systems. No stale data, no manual imports.
Keep Google Cloud Platform and Google Cloud Spanner 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 Google Cloud Spanner'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 Google Cloud Spanner where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Google Cloud Spanner sync into Google Cloud Platform in real time, and result tables in Google Cloud Platform sync back into Google Cloud Spanner, with schema and type mapping between the two systems handled for you.
Rows from Google Cloud Spanner land in Google Cloud Platform as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Google Cloud Platform sync into Google Cloud Spanner, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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.
| Google Cloud Platform objects | Google Cloud Spanner objects | |
|---|---|---|
| Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. | Tables Relational tables mapped one-to-one to sync targets. | |
| Cloud Storage objects Staging area for file-based bulk loads into BigQuery and other services. | Rows The unit of read and write in each sync cycle, keyed by primary key. | |
| Pub/Sub topics Event streams used to move change events between systems in near real time. | Interleaved tables Child rows physically co-located with parents; synced as related records. | |
| Firestore documents Document data read and written through the Firestore API for app-facing syncs. | Secondary indexes Used to make incremental read queries efficient on non-key columns. | |
| Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. | Change streams Capture inserts, updates, and deletes for log-style change data capture. | |
| BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. | Views Read-only projections useful for shaping data before it leaves Spanner. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud Platform–Google Cloud Spanner connection.
Changes in Google Cloud Platform or Google Cloud Spanner instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Google Cloud Platform or Google Cloud Spanner data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Google Cloud Platform or Google Cloud Spanner record.
Track your Google Cloud Platform ⇄ Google Cloud Spanner sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Google Cloud Platform and Google Cloud Spanner.
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 Google Cloud Platform and Google Cloud Spanner 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 Google Cloud Platform and Google Cloud Spanner 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 Google Cloud Platform and Google Cloud Spanner: authenticate both systems, choose the objects to sync (such as Google Cloud Platform's Cloud SQL databases and Cloud Storage objects), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Google Cloud Platform side: Pub/Sub topics, Firestore documents, Spanner tables, BigQuery datasets, plus custom fields where Google Cloud Platform exposes them. On the Google Cloud Spanner side: Rows, Interleaved tables, Secondary indexes, Change streams. Stacksync auto-detects both schemas and converts types between the two systems.
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.
Common patterns for Google Cloud Platform and Google Cloud Spanner: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from Google Cloud Spanner land in Google Cloud Platform as they change, replacing hand-built CDC and batch extract jobs.
Google Cloud Platform: Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols. Authentication: IAM service accounts with OAuth 2.0 tokens. Google Cloud Spanner: GRPC/REST client API with SQL query surface (GoogleSQL and PostgreSQL-interface dialects). Authentication: Google Cloud IAM (service accounts). Stacksync manages authentication, retries, and rate limits on both sides.
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. Google Cloud Spanner: Change streams record row-level inserts, updates, and deletes and can be consumed through the API for CDC pipelines. Stacksync's field mapping accounts for these differences between Google Cloud Platform and Google Cloud Spanner without custom code.
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 Google Cloud Platform and Google Cloud Spanner.