Real-time
Two-way sync
Changes in Airtable or AWS Aurora MySQL instantly reflect in both systems. No stale data, no manual imports.
Database
Airtable to AWS Aurora MySQL integration — real-time, two-way sync
Keep Airtable and AWS Aurora MySQL in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from MuleSoft
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Airtable and AWS Aurora MySQL
Keep Airtable and AWS Aurora MySQL synchronized in real time, across engines, regions, or services, in one or both directions.
Connecting Airtable to AWS Aurora MySQL bridges a no-code workspace and a production relational database. Airtable Records become queryable Rows in Aurora MySQL Tables for analytics and application use, while database data surfaces in Airtable Views for business users who do not write SQL.
Stacksync syncs tables or collections between Airtable and AWS Aurora MySQL 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 Engineering queries Airtable-managed reference data as Aurora MySQL Rows from production services.
- 02 Analysts join Airtable Records with existing Aurora MySQL Tables using standard SQL and Views.
- 03 Ops teams give non-technical staff a safe editing surface over Aurora MySQL data via Airtable Views.
- 04 Use Airtable as a lightweight front end for product catalogs or inventory stored in an ERP or warehouse database.
Common sync patterns
Base-to-database mirror
Airtable Tables and Records replicate into Aurora MySQL Tables and Rows, with Fields mapped to Columns and keys enforced by Primary keys and indexes.
Operational editing layer
business users edit Rows from Aurora MySQL databases (schemas) through Airtable Views, with changes written back to the source Tables.
Schema-aware field sync
new Airtable Fields propagate as Aurora MySQL Columns so downstream queries stay aligned with the base structure.
What you can sync between Airtable and AWS Aurora MySQL
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.
| Airtable objects | AWS Aurora MySQL objects | How this pairing syncs | |
|---|---|---|---|
| Tables Map to sync tables; schema is readable through the base metadata endpoints. | Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Filtered subsets of a table that can scope which records a sync reads. | Views Can serve as read-only sync sources for derived or filtered datasets. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Linked records Cross-table references that carry relationships between synced tables. | Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | Linked records is specific to Airtable and Foreign keys to AWS Aurora MySQL — each maps to any object or custom field on the other side. | |
| Attachments File fields exposed as expiring URLs that syncs can mirror to other systems. | Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | Attachments is specific to Airtable and Stored procedures and triggers to AWS Aurora MySQL — each maps to any object or custom field on the other side. | |
| Collaborators User fields useful for mapping record ownership to accounts in a CRM or database. | Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Collaborators is specific to Airtable and Databases (schemas) to AWS Aurora MySQL — each maps to any object or custom field on the other side. | |
| Bases Top-level containers; each base has its own API endpoint and schema. | Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Bases is specific to Airtable and Rows to AWS Aurora MySQL — each maps to any object or custom field on the other side. |
How changes propagate between Airtable and AWS Aurora MySQL
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.
Airtable AWS Aurora MySQL Sub-second propagation
DetectionAirtable pushes changes as they happen — webhook events backed by change data capture. Incremental updates: changes in Airtable are detected and synced efficiently in realtime (webhook-based — creator role required to create webhooks).
DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.
AWS Aurora MySQL Airtable 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 written to Airtable through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Airtable: The Web API enforces a per-base limit of 5 requests per second.
What ships with Airtable ⇄ AWS Aurora MySQL
Connect Airtable and AWS Aurora MySQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Airtable–AWS Aurora MySQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Airtable or AWS Aurora MySQL 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 Airtable or AWS Aurora MySQL record.
Observability
Monitoring
Track your Airtable ⇄ AWS Aurora MySQL sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Airtable and AWS Aurora MySQL.
How the Airtable and AWS Aurora MySQL connectors work
Airtable
- Integration surface
- REST API (per-base Web API plus metadata and webhooks endpoints)
- Authentication
- OAuth (Airtable OAuth grant to specific bases or all resources); the authorizing user must have a `creator` role, since only creator roles can create webhooks
- Change detection
- Incremental updates: changes in Airtable are detected and synced efficiently in realtime (webhook-based — creator role required to create webhooks); formula fields don't emit change events and are re-synced every hour
- Capabilities
- read · write · CDC · webhooks
- Rate limits
- The Web API enforces a per-base limit of 5 requests per second.
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
How it works
How to connect Airtable to AWS Aurora MySQL — 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.
- 01
Connect your apps
Authenticate Airtable and AWS Aurora MySQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Airtable
connected
AWS Aurora MySQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Airtable and AWS Aurora MySQL 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.
objects · Airtable ⇄ AWS Aurora MySQLCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Airtable AWS Aurora MySQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Airtable and AWS Aurora MySQL integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Airtable and AWS Aurora MySQL: authenticate both systems, choose the objects to sync (such as Airtable's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Airtable and AWS Aurora MySQL records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Airtable and AWS Aurora MySQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Airtable–AWS Aurora MySQL integration in-house.
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Yes — Stacksync ships production-grade connectors for both Airtable and AWS Aurora MySQL. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Airtable: Incremental updates: changes in Airtable are detected and synced efficiently in realtime (webhook-based — creator role required to create webhooks); formula fields don't emit change events and are re-synced every hour. On AWS Aurora MySQL: Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Airtable side: Fields, Views, Linked records, Attachments, plus custom fields where Airtable exposes them. On the AWS Aurora MySQL side: Stored procedures and triggers, Databases (schemas), Tables, Rows. Stacksync auto-detects both schemas and converts types between the two systems.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 485 integrations available for Airtable and AWS Aurora MySQL.
Popular · 6 of 485
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Airtable ⇄ IBM Informix -
Airtable ⇄ InfluxDB -
Airtable ⇄ InterSystems IRIS -
Airtable ⇄ MarkLogic - AWS Aurora MySQL ⇄ MarkLogic
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AWS Aurora MySQL ⇄ Neo4j
No integrations match .
