Airtable and MySQL pipelines

This guide covers both directions between Airtable and MySQL. It uses an explicit destination contract, a published SQL model, and a stable Upsert key for repeatable runs.

Names, emails, companies, and rows shown in code blocks are synthetic fixtures. They are examples, not customer records or live customer activity.

Validated connector routes

The following routes were exercised through the MantrixFlow browser workflow with real source previews and destination verification:

Source	Destination	Result
Airtable	PostgreSQL	Passed
Airtable	MySQL	Passed
Airtable	Airtable	Passed
PostgreSQL	Airtable	Passed
MySQL	Airtable	Passed
Stripe	Airtable	Passed
HubSpot	Airtable	Passed

This is a functional verification matrix, not a throughput benchmark. Validate your own field types, permissions, row volume, and rate-limit behavior before a production rollout.

Shared preparation

Create and test these reusable connections:

An Airtable source connection with schema and record read access.
An Airtable destination connection with schema read plus record read and write access. One token can be reused for both roles when your security policy permits all required scopes and bases.
A MySQL source connection with read access to the source database.
A MySQL destination connection with write access to the destination database and its existing tables.

See Airtable source, Airtable destination, MySQL source, and MySQL destination for least-privilege setup.

Prepare reusable test data

Airtable source table

Create an Airtable table named Customers with these fields:

Field	Type	Example
`External ID`	Single line text	`airtable-001`
`Name`	Single line text	`Airtable Alpha`
`Email`	Email	`alpha@example.test`
`Status`	Single select or Single line text	`active`

Enter at least three records. Keep External ID unique and populated.

Airtable destination table

Create a separate table named Pipeline Sink with these writable fields:

Field	Type	Purpose
`External ID`	Single line text	Upsert merge field
`Name`	Single line text	Mapped display value
`Email`	Email	Mapped email value
`Source`	Single line text	Source lineage
`Notes`	Long text	Verification detail

Do not use a formula or lookup as External ID; merge fields must be writable.

MySQL source table

CREATE DATABASE IF NOT EXISTS source_app
  CHARACTER SET utf8mb4;

CREATE TABLE source_app.customers (
  id varchar(64) PRIMARY KEY,
  name varchar(255) NOT NULL,
  email varchar(320),
  updated_at datetime(6) NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

INSERT INTO source_app.customers (id, name, email, updated_at)
VALUES
  ('mysql-001', 'MySQL Alpha', 'mysql-alpha@example.test', UTC_TIMESTAMP(6)),
  ('mysql-002', 'MySQL Sample B', 'mysql-sample-b@example.test', UTC_TIMESTAMP(6)),
  ('mysql-003', 'MySQL Gamma', 'mysql-gamma@example.test', UTC_TIMESTAMP(6))
ON DUPLICATE KEY UPDATE
  name = VALUES(name),
  email = VALUES(email),
  updated_at = VALUES(updated_at);

MySQL destination table

CREATE DATABASE IF NOT EXISTS analytics
  CHARACTER SET utf8mb4;

CREATE TABLE analytics.airtable_customers (
  external_id varchar(64) PRIMARY KEY,
  name varchar(255),
  email varchar(320),
  airtable_created_at datetime(6)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

Airtable to MySQL

1. Create the pipeline

Open Data Pipelines and click New Pipeline.
Name it Airtable Customers to MySQL.
Choose the Airtable source connection and create the pipeline.

2. Configure Airtable source

Open Source.
Click Load bases and select the base containing Customers.
Select the Customers table.
Preview rows and confirm _airtable_record_id, External ID, Name, and Email appear.
Keep Full table mode and click Save stream settings.

3. Configure MySQL destination

Open Destinations, click Add destination, choose the MySQL connection, set the target database to analytics, and save.
Open Transformations, select the MySQL destination, and create a model using the Airtable source stream.
Use this SQL, replacing the staging relation with the exact lowercase value shown in the editor:

SELECT
  "External ID" AS external_id,
  Name AS name,
  Email AS email,
  _airtable_created_time AS airtable_created_at
FROM {{ source('raw', 'airtable__tblefetdfzjakhuqt') }}
WHERE "External ID" IS NOT NULL
  AND TRIM("External ID") <> ''

Save draft, Validate draft, Preview output, and Publish revision.
Return to the destination editor.
Under Published output targets, set analytics.airtable_customers and select external_id as the Upsert key.
Create/verify the table if needed, then save the destination.

4. Run and verify

Validate the pipeline from Overview, click Run all, and wait for Succeeded in Runs. Then run:

SELECT external_id, name, email, airtable_created_at
FROM analytics.airtable_customers
ORDER BY external_id;

Edit one Airtable name and rerun. The row should update without increasing the count.

MySQL to Airtable

1. Create the pipeline

Create a pipeline named MySQL Customers to Airtable.
Choose the MySQL source connection.

2. Configure MySQL source

Open Source and click Discover catalog.
Enable source_app.customers.
Preview the three test rows.
Use Full table for the first run and click Save stream settings.

3. Add the destination and publish the model

Open Destinations, add and save the Airtable destination connection. Then open Transformations, select it, create a transformation using the MySQL stream, and use:

SELECT
  id AS external_id,
  name,
  email,
  'mysql' AS source,
  CONCAT('Synced from MySQL at ', CAST(updated_at AS VARCHAR)) AS notes
FROM {{ source('raw', 'source_app__customers') }}
WHERE id IS NOT NULL

Save the draft, validate, preview, and publish the revision before configuring the Airtable fields.

4. Map Airtable destination fields

Return to the Airtable destination editor.
Click Load bases, select the destination base, and choose Pipeline Sink.
Under Published output targets, map fields:

SQL output	Airtable field	Merge key
`external_id`	`External ID`	Yes
`name`	`Name`	No
`email`	`Email`	No
`source`	`Source`	No
`notes`	`Notes`	No

Save the destination, validate from Overview, and click Run all.

5. Verify Upsert

Open Pipeline Sink in Airtable and filter External ID by mysql-. Confirm all three records and their mapped values. Update mysql-002 in MySQL, rerun, and confirm Airtable updates the same record rather than creating a duplicate.

Airtable to Airtable

Use separate source and destination tables, even when they are in the same base. Configure Customers as the source and Pipeline Sink as the destination.

SELECT
  CONCAT('airtable-', _airtable_record_id) AS external_id,
  Name AS name,
  Email AS email,
  'airtable' AS source,
  CONCAT('Original record: ', _airtable_record_id) AS notes
FROM {{ source('raw', 'airtable__tblefetdfzjakhuqt') }}

Map external_id to External ID and select it as the merge key. The prefix prevents collisions with IDs from MySQL, Stripe, HubSpot, or other pipelines sharing the same sink table.

Do not target the same Airtable table used as the source. A self-feeding Full Table pipeline can continually expand its own input or overwrite records in ways that are difficult to audit.

Run checklist

Before each run, confirm:

both connections still pass their connection tests;
source discovery shows the expected table;
preview returns representative rows;
the published SQL model uses the staging name shown by the transformation editor;
the database table or Airtable table already exists;
every destination column has a compatible type or field mapping;
the Upsert key is unique and populated for every output row; and
the Runs tab reports failed rows = 0.

Common errors

Error	Cause and fix
`Pipeline not found` while opening discovery	Save the source-only pipeline shell, then reload. Current builds allow `/full` before a destination exists.
`Unable to discover catalog`	Retest the source connection and confirm schema/base access.
MySQL destination table not found	Create the exact `database.table` and validate again.
Airtable destination table not accessible	Restore token resource access or refresh and select the table again.
Airtable field is read-only	Map to a writable field instead of a formula, lookup, or rollup.
Airtable upsert field has no value	Filter empty keys in SQL or choose another merge field.
SQL relation does not exist	Copy the lowercase staging relation from the transformation editor.
Database is locked during concurrent runs	Retry after active work completes and confirm the ELT service includes serialized dbt execution.

Production rollout

After a successful Full Table validation:

Record the source count and destination count.
Rerun unchanged input and confirm no duplicates.
Update a source record and confirm an in-place destination update.
Review the token and database grants for least privilege.
Set an operational schedule only after the manual run is stable.
Monitor Runs for row-count changes, retries, and mapping failures.

Introduction

Getting started

Connections

Connector Reference

Pipelines

Transformations

Scheduling and Sync Modes

Pipeline Runs

Workspace

Billing and Usage

Security and Data Handling

Troubleshooting

Examples and Updates

Airtable and MySQL pipelines

Validated connector routes

Shared preparation

Prepare reusable test data

Airtable source table

Airtable destination table

MySQL source table

MySQL destination table

Airtable to MySQL

1. Create the pipeline

2. Configure Airtable source

3. Configure MySQL destination

4. Run and verify

MySQL to Airtable

1. Create the pipeline

2. Configure MySQL source

3. Add the destination and publish the model

4. Map Airtable destination fields

5. Verify Upsert

Airtable to Airtable

Run checklist

Common errors

Production rollout

​Validated connector routes

​Shared preparation

​Prepare reusable test data

​Airtable source table

​Airtable destination table

​MySQL source table

​MySQL destination table

​Airtable to MySQL

​1. Create the pipeline

​2. Configure Airtable source

​3. Configure MySQL destination

​4. Run and verify

​MySQL to Airtable

​1. Create the pipeline

​2. Configure MySQL source

​3. Add the destination and publish the model

​4. Map Airtable destination fields

​5. Verify Upsert

​Airtable to Airtable

​Run checklist

​Common errors

​Production rollout

Validated connector routes

Shared preparation

Prepare reusable test data

Airtable source table

Airtable destination table

MySQL source table

MySQL destination table

Airtable to MySQL

1. Create the pipeline

2. Configure Airtable source

3. Configure MySQL destination

4. Run and verify

MySQL to Airtable

1. Create the pipeline

2. Configure MySQL source

3. Add the destination and publish the model

4. Map Airtable destination fields

5. Verify Upsert

Airtable to Airtable

Run checklist

Common errors

Production rollout