Two-way sync
Changes in AWS Aurora MySQL instantly reflect in Supabase, and back. No stale data, no manual imports.
Map the fields once, and every write moves both ways in milliseconds. Supabase row inserts land in AWS Aurora MySQL, AWS Aurora MySQL updates land back in Supabase.
Trusted by fast-scaling teams, from YC startups to enterprise platform teams

Connects over SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC, mapped field-by-field into Supabase, with row-level audit and no backend of your own to run.
Every table maps to a AWS Aurora MySQL object both ways. Insert a row in Supabase and it lands in AWS Aurora MySQL; update a record there and Supabase reflects it back.
Log-based CDC via the MySQL binary log. Changes land in Supabase in milliseconds, not on the next polling cycle.
Any object the API exposes can be mapped into Supabase, with schema discovery doing the field-matching for you.
Patterns a two-person team can ship in a week. Any table in Supabase maps to any object in AWS Aurora MySQL.
Changes in AWS Aurora MySQL instantly reflect in Supabase, and back. No stale data, no manual imports.
Two-way sync between Aurora MySQL and Supabase, so application data and CRM records from Salesforce or HubSpot stay aligned without custom API code.
Give backend services read and write access to ERP or billing data by syncing it from Supabase into the Aurora tables the application already queries.
Stream row changes from Aurora MySQL into Supabase, and from Supabase back to SaaS tools, via CDC instead of scheduled batch exports.
Consolidate data from multiple SaaS systems into Supabase, then mirror it into Aurora MySQL as the operational store your product already queries.
No custom ETL jobs, webhooks, or sync scripts to write and maintain. Map Supabase tables to AWS Aurora MySQL objects like Databases and Tables once, and every write stays in sync from there on.
Changes in Supabase reach AWS Aurora MySQL in real time, and back. databases, tables and rows stay consistent everywhere they live.
Your Supabase write-ahead log is read directly, and AWS Aurora MySQL changes are picked up the moment they happen, so sync keeps pace with live traffic. No polling delays, rate limits, or extra load on your database.
OAuth your project and the system. Schemas read automatically.
Tables to objects, fields to fields. Transforms run inline.
Historical backfill, then continuous CDC both ways.
Row-level logs, latency and one-click replay.
One client, the same auth as your Supabase project. If you know the Supabase client, you already know this one.
Read the docsimport { createClient } from '@stacksync/client'const stacksync = createClient( process.env.SUPABASE_URL, process.env.STACKSYNC_API_KEY)export default function Deals() { const [deals, setDeals] = useState([]) useEffect(() => { stacksync.from('deals').select('*') .then(({ data }) => setDeals(data)) }, []) return <DealList items={deals} />}
import { createClient } from '@stacksync/client'export async function POST(request) { const stacksync = createClient( process.env.SUPABASE_URL, process.env.STACKSYNC_API_KEY ) const { id, stage } = await request.json() // writes Supabase, propagates to AWS Aurora MySQL const { data } = await stacksync .from('deals') .update({ stage }) .eq('id', id) return Response.json(data)}
from stacksync import create_clientstacksync = create_client( os.environ['SUPABASE_URL'], os.environ['STACKSYNC_API_KEY'])# one write, both systemsstacksync.table('deals').update( {'stage': 'won', 'amount': 48000}).eq('id', 'd_10427').execute()for row in stacksync.logs('deals').recent(): print(row['system'], row['latency_ms'])
import { createClient } from '@stacksync/client'Deno.serve(async (req) => { const stacksync = createClient( Deno.env.get('SUPABASE_URL'), Deno.env.get('STACKSYNC_API_KEY') ) const { record } = await req.json() await stacksync.from('accounts').upsert({ id: record.id, owner: record.owner_email }) return new Response('ok')})
// claude_desktop_config.json{ "mcpServers": { "stacksync": { "command": "npx", "args": ["-y", "@stacksync/mcp"], "env": { "STACKSYNC_API_KEY": "sk_live_...", "SUPABASE_URL": "https://xyz.supabase.co" } } }}// your agent now reads and writes// every connected system of record
-- Supabase stays the source of truthupdate deals set stage = 'won', amount = 48000 where id = 'd_10427';-- Stacksync picks up the change via CDC-- and writes it to every mapped systemselect system, object_id, latency_ms, status from stacksync.write_log where table_name = 'deals' order by created_at desc limit 10;
Normally $1,000/mo. Yours at $0 during launch week.
Plus $100 in sync credits on the house. No card, no sales call, the same self-serve start you got with Supabase.
Takes about 2 minutes · cancel in one click · export every mapping you build
“We went from treating data integration as a necessary evil that consumed our best engineers to having it just work, reliably, at scale, in real-time.”
Alex Marinov · VP of Technology, ACERTUS
Trusted by 1,000+ teams · SOC 2 Type II · ISO 27001
The integration layer is where compliance reviews stall. Row-level audit, residency and DPF certification for US, EU, UK and CH transfers, so procurement is a form, not a quarter.
Learn more about security
Okta, Azure and Google SSO, with SCIM provisioning.
Sync issues to email, Slack, PagerDuty or WhatsApp, with retry and revert.
Connects to your systems your way.
Stacksync watches your Supabase tables via CDC and AWS Aurora MySQL's API in real time. A write on either side maps to fields on the other and propagates in milliseconds, with row-level logs for every change.
Yes. Changes made in Supabase propagate to AWS Aurora MySQL and vice versa. One-way flows are also supported when a direction should stay read-only.
No. Authenticate both systems, pick objects and fields to map, and enable the sync. Most integrations go live in minutes with no infrastructure to manage.
Stacksync is SOC 2 Type II, ISO 27001, HIPAA, GDPR, CCPA and CSA STAR certified, and holds the EU-US, UK and Swiss Data Privacy Framework (DPF) certification. Data is encrypted in transit, with a zero-persistent-storage architecture: records aren't retained after a sync operation.