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 | How this pairing syncs | |
|---|---|---|---|
| Databases Scope the tables included in a sync configuration. | Databases Instance-level databases that scope a sync's reads and writes. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Schemas Namespace tables in PostgreSQL and SQL Server instances. | Schemas Namespaces (dbo and custom) used to organize synced tables. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. Custom fields on either side are included in the mapping. | |
| Tables Mapped directly to sync targets; schema changes can be propagated. | Tables The primary sync target; rows map to records in connected systems. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Read-only sources for shaping data before syncing it out. | Views Read-side projections used as outbound sync sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| 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. | Transaction logs is specific to Google Cloud SQL and Stored Procedures to SQL Server — each maps to any object or custom field on the other side. | |
| Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. | Columns Field-level mapping targets with T-SQL types. | Instances is specific to Google Cloud SQL and Columns to SQL Server — each maps to any object or custom field on the other side. |
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.
DeliveryEach detected change is applied to SQL Server as a row-level write, with types converted between the two schemas.
DetectionChanges in SQL Server are captured at the source via change data capture — no polling loop against its API. SQL Server Native Change Data Capture (CDC).
DeliveryEach detected change is applied to Google Cloud SQL as a row-level write, with types converted between the two schemas.
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 Databases and Schemas), 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 468 integrations available for Google Cloud SQL and SQL Server.