Cinchy Platform Documentation
Cinchy v5.6

Kafka Topic

1. Overview

Apache Kafka is an end-to-end event streaming platform that:
  • Publishes (writes) and subscribes to (reads) streams of events from sources like databases, cloud services, and software applications.
  • Stores these events durably and reliably for as long as you want.
  • Processes and reacts to the event streams in real-time and retrospectively.
Those events are organized and durably stored in topics. These topics are then partitioned over a number of buckets located on different Kafka brokers.
Event streaming thus ensures a continuous flow and interpretation of data so that the right information is at the right place, at the right time for your key use cases.
Example Use Case: You currently use Kafka to store the metrics for user logins, but being stuck in the Kafka silo means that you can't easily use this data across a range of business use cases or teams. You can use a batch sync in order to liberate your data into Cinchy.
The Kafka Topic source supports batch syncs.

2. Info Tab

You can review the parameters that can be found in the info tab below (Image 1).


Mandatory. Input a name for your data sync
Website Metrics
Mandatory. This is a pre-populated field containing a version number for your data sync. You can override it if you wish.
Optional. Review our documentation on Parameters here for more information about this field.
Image 1: The Info Tab

3. Source Tab

The following table outlines the mandatory and optional parameters you will find on the Source tab.
Source Details
The following parameters will help to define your data sync source and how it functions.
Mandatory. Select your source from the drop down menu.
Kafka Topic
The Schema section is where you define which source columns you want to sync in your connection. You can repeat the values for multiple columns.
Mandatory. The name of your column as it appears in the source.
Optional. You may choose to use an alias on your column so that it has a different name in the data sync.
Data Type
Mandatory. The data type of the column values.
Optional. You may choose to add a description to your column.
There are other options available for the Schema section if you click on Show Advanced.
  • If both Mandatory and Validated are checked on a column, then rows where the column is empty are rejected
  • If just Mandatory is checked on a column, then all rows are synced with the execution log status of failed, and the source error of "Mandatory Rule Violation"
  • If just Validated is checked on a column, then all rows are synced.
Validate Data
  • If both Mandatory and Validated are checked on a column, then rows where the column is empty are rejected
  • If just Validated is checked on a column, then all rows are synced.
Trim Whitespace
Optional if data type = text. If your data type was chosen as "text", you can choose whether to trim the whitespace (that is, spaces and other non-printing characters).
Max Length
Optional if data type = text. You can input a numerical value in this field that represents the maximum length of the data that can be synced in your column. If the value is exceeded, the row will be rejected (you can find this error in the Execution Log).
You can choose to add in a Transformation > String Replacement by inputting the following:
Mandatory if using a Transformation. The pattern for your string replacement, i.e. the string that will be searched and replaced.
What you want to replace your pattern with.
Note that you can have more than one String Replacement
You have the option to add a source filter to your data sync. Please review the documentation here for more information on source filters.

4. Next Steps