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Database

AWS Aurora MySQL to Supabase integration — real-time, two-way sync

Keep AWS Aurora MySQL and Supabase 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 AWS Aurora MySQL and Supabase

Keep AWS Aurora MySQL and Supabase synchronized in real time, across engines, regions, or services, in one or both directions.

Teams sync AWS Aurora MySQL with Supabase when a product runs on Supabase but other systems or services live on Aurora MySQL. The sync keeps Tables and Rows consistent across both, including Supabase auth.users and JSONB Columns alongside Aurora MySQL Tables and Primary keys and indexes.

Stacksync syncs tables or collections between AWS Aurora MySQL and Supabase 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.

Common use cases

  • 01 Run a Supabase-backed product alongside services on Aurora MySQL with one consistent dataset.
  • 02 Expose Supabase application data to Aurora MySQL consumers while Row Level Security Policies keep the Supabase side controlled.
  • 03 Migrate workloads between Aurora MySQL and Supabase with both databases live.
  • 04 Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.

Common sync patterns

Cross-database table sync

Aurora MySQL Tables and Rows replicate into Supabase Tables within the mapped Schemas, and back.

User data consolidation

Supabase auth.users records sync into an Aurora MySQL Table so backend services share one user reference.

Semi-structured data handoff

Supabase JSONB Columns map to Aurora MySQL Columns so both applications read the same payloads.

What you can sync between AWS Aurora MySQL and Supabase

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.

AWS Aurora MySQL objects Supabase objects How this pairing syncs
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Tables Standard Postgres tables; the primary two-way sync target. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Can serve as read-only sync sources for derived or filtered datasets. Views Read-side projections exposed to outbound syncs. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. auth.users Managed authentication users, often mirrored into CRM or support systems. Primary keys and indexes is specific to AWS Aurora MySQL and auth.users to Supabase — each maps to any object or custom field on the other side.
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Row Level Security Policies Row-level access rules that govern what the REST layer exposes. Foreign keys is specific to AWS Aurora MySQL and Row Level Security Policies to Supabase — each maps to any object or custom field on the other side.
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. JSONB Columns Semi-structured payloads such as event properties or nested objects. Stored procedures and triggers is specific to AWS Aurora MySQL and JSONB Columns to Supabase — each maps to any object or custom field on the other side.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Database Functions Postgres functions that can transform or validate synced rows. Databases (schemas) is specific to AWS Aurora MySQL and Database Functions to Supabase — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL and Supabase

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.

AWS Aurora MySQL Supabase Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

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

Supabase AWS Aurora MySQL Sub-second propagation

DetectionSupabase pushes changes as they happen — webhook events backed by change data capture. Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime.

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

Rate-limit considerations

  • Supabase: SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits.
What ships with AWS Aurora MySQL ⇄ Supabase

Connect AWS Aurora MySQL and Supabase for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–Supabase connection.

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Supabase instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora MySQL or Supabase 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 AWS Aurora MySQL or Supabase record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Supabase sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and Supabase.

How the AWS Aurora MySQL and Supabase connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
Capabilities
read · write · CDC

Supabase

Integration surface
Direct PostgreSQL wire protocol connection, plus an auto-generated REST API (PostgREST)
Authentication
Database credentials (connection string) for SQL access; API keys (anon / service role) for the REST layer
Change detection
Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime; database webhooks can also fire on row changes
Capabilities
read · write · CDC · webhooks
Rate limits
SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits
How it works

How to connect AWS Aurora MySQL to Supabase — 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 AWS Aurora MySQL and Supabase 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
    AWS Aurora MySQL connected
    Supabase connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL and Supabase 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 · AWS Aurora MySQL ⇄ Supabase
    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
    AWS Aurora MySQL Supabase
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL and Supabase 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 484 integrations available for AWS Aurora MySQL and Supabase.

Popular · 8 of 484
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