Two-way sync
Changes in Google Cloud SQL or SQL Server instantly reflect in both systems. No stale data, no manual imports.
Keep Google Cloud SQL and SQL Server in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Google Cloud SQL and SQL Server continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Keep the same dataset live in both Google Cloud SQL and SQL Server, so each workload runs on the engine that suits it.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
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 SQL objects | SQL Server objects | |
|---|---|---|
| Schemas Namespace tables in PostgreSQL and SQL Server instances. | Views Read-side projections used as outbound sync sources. | |
| Tables Mapped directly to sync targets; schema changes can be propagated. | Columns Field-level mapping targets with T-SQL types. | |
| Rows Read and written by primary key during each sync cycle. | Primary and Unique Keys Match keys for idempotent upserts and conflict handling. | |
| Views Read-only sources for shaping data before syncing it out. | CDC Change Tables System-populated tables holding captured inserts, updates, and deletes for consumers. | |
| Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. | Stored Procedures T-SQL logic that can validate or post-process synced rows. | |
| Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. | Databases Instance-level databases that scope a sync's reads and writes. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud SQL–SQL Server connection.
Changes in Google Cloud SQL or SQL Server instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Google Cloud SQL or SQL Server 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 SQL or SQL Server record.
Track your Google Cloud SQL ⇄ SQL Server sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Google Cloud SQL and SQL Server.
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 SQL and SQL Server 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 SQL and SQL Server 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 SQL and SQL Server: authenticate both systems, choose the objects to sync (such as Google Cloud SQL's Schemas and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Google Cloud SQL: Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback. On SQL Server: SQL Server Native Change Data Capture (CDC); a DBA runs a one-time setup script with sysadmin privileges to enable CDC and create Stacksync wrapper procedures. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Google Cloud SQL side: Views, Transaction logs, Instances, Databases, plus custom fields where Google Cloud SQL exposes them. On the SQL Server side: Databases, Schemas, Tables, Views. 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 SQL and SQL Server: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both Google Cloud SQL and SQL Server, so each workload runs on the engine that suits it.
Google Cloud SQL: Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management. Authentication: Database credentials; IAM database authentication is available for MySQL and PostgreSQL. SQL Server: SQL over the TDS wire protocol (Tabular Data Stream), via ODBC/JDBC/ADO.NET drivers. Authentication: Database credentials entered as a connection string or as parameters (host/user/password) in the Create New Sync page. Stacksync manages authentication, retries, and rate limits on both sides.
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 SQL and SQL Server.