Does Databricks have an estimated timeline or roadmap for when the MySQL, Oracle, and PostgreSQL Lakeflow Connect connectors will reach GA? Any information would be helpful. Thanks!

@Rongali_Vasu, @gowri_databrick 

While waiting for Lakeflow Connect connectors for MySQL, Oracle, or PostgreSQL to become GA, one alternative is to use JDBC connections from Databricks. This can work with most RDBMS platforms that provide a JDBC driver.

For example, you can use PySpark to read from an RDBMS:

jdbc_url = "jdbc:postgresql://<host>:5432/<database>"

connection_properties = {
"user": "<username>",
"password": "<password>",
"driver": "org.postgresql.Driver"
}

df = (
spark.read
.jdbc(
url=jdbc_url,
table="public.customer",
properties=connection_properties
)
)

display(df)

The same approach can be used for other databases such as MySQL or Oracle by changing the JDBC URL and driver.

For production workloads, I would avoid hardcoding credentials and instead use a secret scope, Key Vault, or another supported credential-management approach.

JDBC is not a replacement for all the capabilities that Lakeflow Connect provides, especially around managed ingestion and CDC, but it can be a practical option when you need to connect to an RDBMS before the required connector is generally available.

Hey there @gowri_databrick 

The query-based Lakeflow Connect connectors for MySQL, Oracle, and PostgreSQL are generally available:

Release Notes 

The CDC versions are presently at different preview stages. MySQL and PostgreSQL are in Public Preview, while Oracle CDC is still in Beta.