MySQL Connector

Standard relational connector for MySQL and MySQL-compatible databases (MariaDB, Aurora MySQL, etc.).

What it lets you do

Test that DagFlux can reach your MySQL server.
List schemas, tables, and views.
List columns of any table with type, nullability, and primary-key flag.
Run any SQL query.
Stream large query results in batches without loading everything into memory.
Insert rows in bulk inside a transaction.

Connection form

Field	Required	Sensitive	Default
Host	Yes	Yes	—
Port	Yes	No	3306
Database	Yes	No	—
Username	Yes	Yes	—
Password	Yes	Yes	—
Use SSL	No	No	false

Connection pooling caps at ten concurrent connections per saved connection so repeated queries don't pay reconnection cost.

Setting up credentials

Step 1 — Connect as a privileged user

Open mysql or any SQL client as a user with GRANT OPTION on the target database (commonly root).

Step 2 — Create a dedicated user

-- Replace the password with a strong one of your own
CREATE USER 'dagflux'@'%' IDENTIFIED BY 'choose-a-strong-password';

The '%' host allows the user to connect from any IP. If you want to restrict it to a specific network, replace '%' with the CIDR or hostname.

Step 3 — Grant read + write access

-- Read + write on every table in the database
GRANT SELECT, INSERT, UPDATE, DELETE ON mydb.* TO 'dagflux'@'%';

-- Allow creating new tables (needed for new-table transformations and joins)
GRANT CREATE, DROP, ALTER, INDEX ON mydb.* TO 'dagflux'@'%';

FLUSH PRIVILEGES;

Step 4 — Read-only variant

If you'll only use the connection for sources:

GRANT SELECT ON mydb.* TO 'dagflux'@'%';
FLUSH PRIVILEGES;

Step 5 — Allow network access

If your MySQL server is firewalled, make sure your machine's IP is allowed (in your provider's security group, in iptables, in the cloud console firewall, etc.). For SSL-only servers, enable the SSL checkbox in the form.

Step 6 — Enter the credentials in DagFlux

Use the user and password you created. Enter the database name. Leave the port at 3306 unless your server uses a custom port.

How transformations are generated

When you ask the AI to transform data sitting in MySQL, the assistant uses prompts written specifically for MySQL. The shape of the result follows the same patterns as PostgreSQL — see PostgreSQL for the breakdown of new-table vs in-place, and database-vs-local storage.