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Push data to Timeplus via Kafka Connect

Kafka Connect is a framework for connecting Kafka with external systems such as databases, key-value stores, search indexes, and file systems, using so-called Connectors.

Kafka Connectors are ready-to-use components, which can help data teams to import data from external systems into Kafka topics and export data from Kafka topics into external systems.

A Kafka Connect plugin for Timeplus is provided to continuously send data from Kafka topics to Timeplus Cloud or self-managed Timeplus deployment, no matter if you run Kafka in the cloud or on-prem.

Depending on how you run Kafka (with open-source Kafka, Confluent Platform, Confluent Cloud, or Redpanda), you can check the corresponding documentation to set up the Kafka Connect.

Setup with Apache Kafka

For example, if you are using open-source Kafka, please check

As a reference, the step-by-step instructions to setup Kafka, Kafka Connect and the Kafka Connect plugin for Timeplus are:

  1. Make sure you have Java installed, say openjdk 17.0.5.
  2. Download the latest Kafka binary from, say kafka_2.13-3.3.1.tgz.
  3. Unarchive the file and open a terminal window and change directory to this folder.
  4. Start the ZooKeeper service via bin/ config/
  5. Open another terminal session and start the Kafka broker service via bin/ config/
  6. Open another terminal session and create a topic bin/ --create --topic my_topic --bootstrap-server localhost:9092
  7. Download the latest kafka-connect-timeplus JAR file and put it in a new folder, say kakfa-connect-jars.
  8. Edit the config/ file and uncomment the last line and point it to your folder, e.g. plugin.path=/Users/name/Dev/kakfa-connect-jars
  9. Create an API key in your Timeplus workspace and create a like this:
name: TimeplusSink
connector.class: com.timeplus.kafkaconnect.TimeplusSinkConnector
tasks.max: 1
topics: my_topic
timeplus.sink.workspace: abc123
timeplus.sink.apikey: 60_char_API_Key data_from_kafka
timeplus.sink.createStream: true
timeplus.sink.dataFormat: raw
  1. Start the Kafka Connect service with the Timeplus Kafka Connect plugin via bin/ config/ config/ It will move data in my_topic to the data_from_kakfa stream in the remote Timeplus. (You can produce sample event via kcat -P -b localhost:9092 -t my_topic enter some lines and produce the data via Ctrl+D)

Setup with Confluent Platform

  1. Make sure you have Java installed, only 1.8 or 1.11 is supported.

  2. Install Confluent Platform per official documentation. Download the zip file from Then install it with confluent-hub install /path/to/

  3. Start the Confluent Platform via confluent local services start

  4. Access the Control Center via http://localhost:9021/ and create a topic say my_topic

  5. Choose Connect menu item and click the Add connector button. Choose the TimeplusSinkConnector tile, and input the settings as:

    1. Topics: my_topic

    2. Name: any name is okay

    3. Tasks max: 1

    4. Key and Value converter class:

    5. Scroll down to the Timeplus section and set the Timeplus server address, workspace, API Key, etc.

    6. Click Next, you can preview the JSON configuration as these:

      "name": "TimeplusSink1",
      "config": {
      "name": "TimeplusSink1",
      "connector.class": "com.timeplus.kafkaconnect.TimeplusSinkConnector",
      "tasks.max": "1",
      "key.converter": "",
      "value.converter": "",
      "topics": "my_topic",
      "timeplus.sink.address": "",
      "timeplus.sink.workspace": "abc123",
      "timeplus.sink.apikey": "60_char_API_Key",
      "timeplus.sink.createStream": "false",
      "": "data_from_kafka",
      "timeplus.sink.dataFormat": "raw"
  6. Click Launch button, in a few seconds, you should see the connector is running.

  7. You can open the Query Console in Timeplus and run a streaming query like SELECT * FROM data_from_kafka. Then create a message in Confluent Control Center (choose Topics, select the my_topic, choose Messages tab, and produce a sample message). Almost in the same time, the message will appear in the Timeplus Console.