Hi,
I suggest taking a look at GoldenGate for Big Data Kafka Handler
<https://docs.oracle.com/en/middleware/goldengate/big-data/19.1/gadbd/using-kafka-handler.html>
(provided
you have a license).
Kind Regards,
Lucas Pimentel Lellis
On Tue, Jul 5, 2022 at 3:55 PM Lok P <loknath.73@xxxxxxxxx> wrote:
Hello All, We have a requirement to stream data from an OLTP database(It's
in Oracle 19C) to the redshift data warehouse in AWS cloud through Kafka
streaming.
Team is planning to move the data using JSON format by clubbing all the
required fields. And as the newly inserted data is coming from one source
so it looks fine to form the JSON and pass it through Kafka stream for the
newly inserted records. But the Updates are happening in the source Oracle
database , from multiple places(From GUI and batch jobs etc) and it would
be a challenge to have the code added in all of those places to pass those
updates to kafka stream through JSON.
Team is planning to use triggers for this purpose. We already have a bunch
of triggers in many tables. (Say for e.g. one table has 7 Update and 1
Delete trigger and few of them have some business logic written in them).
And we have seen DML slowness because of the trigger code in this
application in the past. But Dev team planning, using additional Oracle
triggers for tracking the DML's here and then creating the JSON elements
and passing those to Kafka through oracle AQ's as the data streaming option
in this scenario. So my question is , is there any other better approach
for streaming the data here or is the trigger approach a suitable one?
