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Database ⇄ Data warehouse

Amazon RDS to Snowflake integration — real-time, two-way sync

Keep Amazon RDS and Snowflake in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon RDS and Snowflake

Connect Amazon RDS and Snowflake with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Teams connect Amazon RDS and Snowflake to move operational data from a transactional database into an analytics warehouse without maintaining custom pipelines. RDS Tables and Views feed Snowflake Schemas and Tables, where Materialized Views and Streams support downstream reporting and change tracking.

Stacksync covers both directions with one connection. Tables or collections in Amazon RDS sync into Snowflake in real time, and result tables in Snowflake sync back into Amazon RDS, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Consolidate multiple RDS Databases into a single Snowflake analytics environment.
  • 02 Retire hand-built ETL scripts that copy RDS Tables into Snowflake on a schedule.
  • 03 Give analysts warehouse access to production data without granting direct RDS connections.
  • 04 Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL

Common sync patterns

Warehouse replication

RDS Tables and Views land in Snowflake Schemas on a continuous sync, preserving Columns and Primary and Unique Keys.

Change capture for analytics

updates to RDS Tables propagate into Snowflake Streams so downstream jobs process only changed rows.

Reporting layer refresh

synced RDS data keeps Snowflake Materialized Views current for BI consumption.

What you can sync between Amazon RDS and Snowflake

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 Snowflake objects How this pairing syncs
Databases Engine-level databases on the instance that scope a sync's reads and writes. Databases Top-level containers that scope which data a sync can touch. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces within a database used to isolate synced tables. Schemas Namespaces within a database used to organize synced tables. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables The core sync target; rows map to records in connected SaaS systems. Tables The main landing and activation target for synced records. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Read-side projections exposed to outbound syncs. Views Modeled projections used as the source side of outbound syncs. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Columns Field-level mapping targets, typed per the underlying engine. Materialized Views Precomputed results synced outward for low-latency reads. Columns is specific to Amazon RDS and Materialized Views to Snowflake — each maps to any object or custom field on the other side.
Primary and Unique Keys Match keys for idempotent upserts. Streams Row-level change records on a table, consumed to process deltas instead of full scans. Primary and Unique Keys is specific to Amazon RDS and Streams to Snowflake — each maps to any object or custom field on the other side.

How changes propagate between Amazon RDS and Snowflake

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.

Amazon RDS Snowflake Sub-second propagation

DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.

DeliveryEach detected change is applied to Snowflake as a row-level write, with types converted between the two schemas.

Snowflake Amazon RDS Sub-second propagation

DetectionChanges in Snowflake are captured at the source via change data capture — no polling loop against its API. The setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism.

DeliveryEach detected change is applied to Amazon RDS as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon RDS: No API rate limits; throughput depends on instance class, storage IOPS, and connection limits.
  • Snowflake: No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time.
What ships with Amazon RDS ⇄ Snowflake

Connect Amazon RDS and Snowflake for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon RDS–Snowflake connection.

Real-time

Two-way sync

Changes in Amazon RDS or Snowflake instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon RDS or Snowflake data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Amazon RDS or Snowflake record.

Observability

Monitoring

Track your Amazon RDS ⇄ Snowflake sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon RDS and Snowflake.

How the Amazon RDS and Snowflake connectors work

Amazon RDS

Integration surface
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
Change detection
Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC; enabled through RDS parameter groups, with polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance class, storage IOPS, and connection limits

Snowflake

Integration surface
SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
Authentication
Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
Change detection
Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
Capabilities
read · write · CDC
Rate limits
No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
Snowflake setup guide
How it works

How to connect Amazon RDS to Snowflake — three steps, no code

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.

  1. 01

    Connect your apps

    Authenticate Amazon RDS and Snowflake with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon RDS connected
    Snowflake connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon RDS and Snowflake 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon RDS ⇄ Snowflake
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon RDS Snowflake
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon RDS and Snowflake integration FAQ

SECURITY

Security teams trust Stacksync

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.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 495 integrations available for Amazon RDS and Snowflake.

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