Integrations for plain-English data pipelines
12 live connectors — 10 pair guides with step-by-step setup — PostgreSQL & MySQL with real-time CDC, AWS S3, Google Sheets, and the SaaS tools your team already pays for: Shopify, Stripe, HubSpot, GitHub, Slack, Notion, Linear, Pipedrive. Don't see yours? The AI Connector Builder generates a working MCP connector from any REST or GraphQL docs URL in minutes.
Popular pipelines
Step-by-step guides for the most common source-to-destination pairs — auth setup, exact resources synced, and the destination schema rsync.ai produces.
Shopify → MySQL
View guide →Shopify → PostgreSQL
View guide →Shopify → Google Sheets
View guide →Stripe → PostgreSQL
View guide →Postgres → MySQL
View guide →Postgres → AWS S3
View guide →Postgres → Google Sheets
View guide →MySQL → PostgreSQL
View guide →MySQL → AWS S3
View guide →MySQL → Google Sheets
View guide →All Shopify integrations
View guide →All PostgreSQL integrations
View guide →All MySQL integrations
View guide →Featured source connector
Each source-and-destination pair has its own page with auth setup, the exact resources synced, sync-mode options (batch or CDC), and the destination schema layout rsync.ai produces.
Sync Shopify orders, customers, products, inventory and fulfillments to any destination — full backfill, incremental updates, and PII safe by default.
Sync Stripe charges, customers, subscriptions, invoices, and payment intents to your database — scheduled batch with cursor pagination, no per-row fees.
Real-time CDC from PostgreSQL via logical replication. Capture every INSERT, UPDATE, DELETE sub-second. Works with RDS, Aurora, Supabase, Neon, and self-hosted Postgres.
Real-time CDC from MySQL via binlog ROW replication. GTID support. Works with MySQL 5.7+, RDS, Aurora, Cloud SQL, and PlanetScale.
All available connectors
Connectors are grouped by what they do. The same connector can be a source, a destination, or both, depending on the pipeline you describe.
Databases with real-time CDC
Logical-replication CDC for transactional sources. Subsecond change capture, transactional consistency, and replayable event history. Both source and destination.
Storage & spreadsheets
Object storage and shareable spreadsheets. Useful as both source and destination for backups, analytics handoff, and ad-hoc reporting.
SaaS & API connectors
First-party connectors for the SaaS tools most teams already pay for. Auth, schema discovery, and pagination handled — no manual API wrappers.
How a rsync.ai integration runs
Every connector — built-in or AI-generated — follows the same three steps. The chat agent does the heavy lifting; you stay in control of the decisions that matter.
Describe the sync in plain English
Say "sync Shopify orders to Postgres every hour" in the chat. No YAML, no DAG, no Python operator to write.
Approve the discovered schema
rsync.ai introspects the source, proposes destination tables with column types and row-count estimates, and waits for you to tick the resources you want.
Run, monitor, and replay
Pipelines emit OpenTelemetry traces to SigNoz. Every run is replayable from the Kafka + Temporal event log, so a bad sync is a one-click rewind.
Don't see your connector?
Point the AI Tool Generator at any REST or GraphQL docs URL and it produces a versioned MCP connector — auth, schema discovery, cursor pagination, and a Dockerfile included. Most APIs are ready to sync in under five minutes.
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