Two-way sync
Changes in Amazon RDS or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon RDS 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 Amazon RDS'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 Amazon RDS where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Amazon RDS sync into Google Cloud Platform in real time, and result tables in Google Cloud Platform sync back into Amazon RDS, 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 Amazon RDS focused on its operational workload.
Rows from Amazon RDS 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.
| Amazon RDS objects | Google Cloud Platform objects | |
|---|---|---|
| Schemas Namespaces within a database used to isolate synced tables. | Cloud Storage objects Staging area for file-based bulk loads into BigQuery and other services. | |
| Tables The core sync target; rows map to records in connected SaaS systems. | Pub/Sub topics Event streams used to move change events between systems in near real time. | |
| Views Read-side projections exposed to outbound syncs. | Firestore documents Document data read and written through the Firestore API for app-facing syncs. | |
| Columns Field-level mapping targets, typed per the underlying engine. | Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. | |
| Primary and Unique Keys Match keys for idempotent upserts. | BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. | |
| Read Replicas Low-impact read endpoints often used as the source side of a sync. | BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon RDS–Google Cloud Platform connection.
Changes in Amazon RDS or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon RDS 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 Amazon RDS or Google Cloud Platform record.
Track your Amazon RDS ⇄ Google Cloud Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon RDS 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 Amazon RDS 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 Amazon RDS 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 Amazon RDS and Google Cloud Platform: authenticate both systems, choose the objects to sync (such as Amazon RDS's Schemas and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Google Cloud Platform side: BigQuery tables, Cloud SQL databases, Cloud Storage objects, Pub/Sub topics, plus custom fields where Google Cloud Platform exposes them. On the Amazon RDS side: Columns, Primary and Unique Keys, Read Replicas, Stored Procedures. 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 Amazon RDS and Google Cloud Platform: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Amazon RDS: SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle). Authentication: Database credentials over SSL/TLS, or IAM database authentication on supported engines. 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. Stacksync manages authentication, retries, and rate limits on both sides.
Google Cloud Platform: Cloud SQL Postgres and MySQL expose log-based CDC (logical replication and binlog), which Datastream and external sync tools consume for real-time replication. Amazon RDS: CDC prerequisites such as binlog row format or logical replication are configured through RDS parameter groups, since superuser access is not provided. Stacksync's field mapping accounts for these differences between Amazon RDS and Google Cloud Platform 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 Amazon RDS and Google Cloud Platform.