Real-time
Two-way sync
Changes in Airtable or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Database
Airtable to AWS Aurora PostgreSQL integration — real-time, two-way sync
Keep Airtable and AWS Aurora PostgreSQL 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
Case study
Migrated from MuleSoft
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Airtable and AWS Aurora PostgreSQL
Keep Airtable and AWS Aurora PostgreSQL synchronized in real time, across engines, regions, or services, in one or both directions.
Teams sync Airtable with AWS Aurora PostgreSQL to keep a business-managed base and a production Postgres database on the same data. Airtable Records land as Rows in Aurora PostgreSQL Tables under governed Databases and schemas, and database changes appear back in Airtable Views without manual exports.
Stacksync syncs tables or collections between Airtable and AWS Aurora PostgreSQL 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 Product teams read Airtable-curated configuration as Aurora PostgreSQL Rows directly from application code.
- 02 Data teams enforce integrity on Airtable-sourced data using Aurora PostgreSQL Primary keys and constraints.
- 03 Analysts build materialized views over synced Airtable Tables for scheduled reporting.
- 04 Use Airtable as a lightweight front end for product catalogs or inventory stored in an ERP or warehouse database.
Common sync patterns
Records-to-rows replication
Airtable Tables and Records sync into Aurora PostgreSQL Tables and Rows, with Primary keys and constraints guaranteeing uniqueness.
Reporting surface
Aurora PostgreSQL Views and materialized views expose curated data that business users browse and edit through Airtable Views.
Linked-record relational mapping
Airtable Linked records translate to constraint-backed relationships across Aurora PostgreSQL Tables.
What you can sync between Airtable and AWS Aurora PostgreSQL
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 PostgreSQL objects | How this pairing syncs | |
|---|---|---|---|
| Tables Map to sync tables; schema is readable through the base metadata endpoints. | Tables The core sync unit; rows are matched across systems by primary key. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Fields Typed columns including linked records, lookups, and rollups; computed fields are read-only in syncs. | Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Fields is specific to Airtable and Views and materialized views to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Views Filtered subsets of a table that can scope which records a sync reads. | Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Views is specific to Airtable and Foreign keys to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Linked records Cross-table references that carry relationships between synced tables. | Replication slots and publications The logical replication objects that power log-based CDC. | Linked records is specific to Airtable and Replication slots and publications to AWS Aurora PostgreSQL — 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. | Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Attachments is specific to Airtable and Databases and schemas to AWS Aurora PostgreSQL — 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. | Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Collaborators is specific to Airtable and Rows to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. |
How changes propagate between Airtable and AWS Aurora PostgreSQL
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 PostgreSQL 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 PostgreSQL as a row-level write, with types converted between the two schemas.
AWS Aurora PostgreSQL Airtable Sub-second propagation
DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling 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 PostgreSQL
Connect Airtable and AWS Aurora PostgreSQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Airtable–AWS Aurora PostgreSQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Airtable or AWS Aurora PostgreSQL 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 PostgreSQL record.
Observability
Monitoring
Track your Airtable ⇄ AWS Aurora PostgreSQL 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 PostgreSQL.
How the Airtable and AWS Aurora PostgreSQL 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 PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
- Capabilities
- read · write · CDC
How it works
How to connect Airtable to AWS Aurora PostgreSQL — 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 PostgreSQL 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 PostgreSQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Airtable and AWS Aurora PostgreSQL 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 PostgreSQLCustomers 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 PostgreSQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Airtable and AWS Aurora PostgreSQL integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Airtable and AWS Aurora PostgreSQL: authenticate both systems, choose the objects to sync (such as Airtable's Tables and Fields), 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 PostgreSQL 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 PostgreSQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Airtable–AWS Aurora PostgreSQL integration in-house.
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Yes — Stacksync ships production-grade connectors for both Airtable and AWS Aurora PostgreSQL. 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 PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling 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: Tables, Records, Fields, Views, plus custom fields where Airtable exposes them. On the AWS Aurora PostgreSQL side: Replication slots and publications, Databases and 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 487 integrations available for Airtable and AWS Aurora PostgreSQL.
Popular · 5 of 487
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Airtable ⇄ Google Cloud SQL -
Airtable ⇄ IBM AS/400 -
Airtable ⇄ IBM Informix -
Airtable ⇄ InfluxDB -
AWS Aurora PostgreSQL ⇄ Neo4j
No integrations match .
