HEAVY-AI (Formerly OmniSci) Sink Connector for Confluent Platform

The Kafka Connect HEAVY-AI Sink connector allows you to export data from Apache Kafka® topics to HEAVY-AI. The connector polls data from Kafka to write to HEAVY-AI based on the topics subscription.


The HEAVY-AI Sink connector includes the following features:

At least once delivery

This connector guarantees that records from the Kafka topic are delivered at least once.

Dead Letter Queue

This connector supports the Dead Letter Queue (DLQ) functionality. For information about accessing and using the DLQ, see Confluent Platform Dead Letter Queue.

Multiple tasks

The HEAVY-AI Sink connector supports running one or more tasks. You can specify the number of tasks in the tasks.max configuration parameter. This can lead to performance gains when multiple files need to be parsed.


  • This connector can only insert data into HEAVY-AI. Updates are not supported.
  • If auto.create is enabled, the default values for fields are ignored. This is because HEAVY-AI does not allow default values for columns.
  • If auto.evolve is enabled, the connector can only add new columns for fields that are marked optional. Mandatory fields are not supported, even if they have default values.
  • Deletion of fields is not supported. You cannot even delete a field that was previously optional. If you must delete fields, manually delete the columns from the corresponding HEAVY-AI table.
  • This connector can not alter the type of an existing column.

Install the HEAVY-AI Connector

You can install this connector by using the confluent connect plugin install command, or by manually downloading the ZIP file.


  • You must install the connector on every machine where Connect will run.

  • An installation of the latest (latest) connector version.

    To install the latest connector version, navigate to your Confluent Platform installation directory and run the following command:

    confluent connect plugin install confluentinc/kafka-connect-omnisci:latest

    You can install a specific version by replacing latest with a version number as shown in the following example:

    confluent connect plugin install confluentinc/kafka-connect-omnisci:1.0.2

Install the connector manually

Download and extract the ZIP file for your connector and then follow the manual connector installation instructions.


You can use this connector for a 30-day trial period without a license key.

After 30 days, you must purchase a connector subscription which includes Confluent enterprise license keys to subscribers, along with enterprise-level support for Confluent Platform and your connectors. If you are a subscriber, you can contact Confluent Support at support@confluent.io for more information.

For license properties, see Confluent Platform license. For information about the license topic, see License topic configuration.

Configuration Properties

For a complete list of configuration properties for this connector, see HEAVY-AI (Formerly OmniSci) Sink Connector Configuration Properties.

For an example of how to get Kafka Connect connected to Confluent Cloud, see Connect Self-Managed Kafka Connect to Confluent Cloud.

Quick Start

In this quickstart, you copy Avro data from a single topic to a local HEAVY-AI database running on Docker.

This example assumes you are running Kafka and Schema Registry locally on the default ports. It also assumes your have Docker installed and running.

First, bring up HEAVY-AI database by running the following Docker command:

docker run -d -p 6274:6274 omnisci/core-os-cpu:v4.7.0

This starts the CPU-based community version of HEAVY-AI, and maps it to port 6274 on localhost. By default, the user name is admin and the password is HyperInteractive. The default database is omnisci.

Start the Confluent Platform using the Confluent CLI command below.


The command syntax for the Confluent CLI development commands changed in 5.3.0. These commands have been moved to confluent local. For example, the syntax for confluent start is now confluent local services start. For more information, see confluent local.

confluent local services start

Property-based example

Next, create a configuration file for the connector. This configuration is used typically along with standalone workers. This file is included with the connector in ./etc/kafka-connect-omnisci/omnisci-sink-connector.properties and contains the following settings:


The first few settings are common settings you specify for all connectors, except for topics which are specific to sink connectors like this one.

The connection.url, connection.user and connection.password specify the connection URL, username, and password of the local HEAVY-AI database. Since auto.create is enabled, the connector creates the table if it is not present.

Run the connector with this configuration.

confluent load OmnisciSinkConnector -d etc/kafka-connect-omnisci/omnisci-sink-connector.properties

REST-based example

This configuration is used typically along with distributed workers. Write the following json to omnisci-sink-connector.json, configure all of the required values, and use the command below to post the configuration to one the distributed connect worker(s). Check here for more information about the Kafka Connect REST API

      "name" : "OmnisciSinkConnector",
      "config" : {
            "connector.class" : "io.confluent.connect.omnisci.OmnisciSinkConnector",
            "tasks.max" : "1",
            "topics": "orders",
            "connection.database": "omnisci",
            "connection.port": "6274",
            "connection.host": "localhost",
            "connection.user": "admin",
            "connection.password": "HyperInteractive",
            "confluent.topic.bootstrap.servers": "localhost:9092",
            "confluent.topic.replication.factor": "1",
            "auto.create": "true"

Use curl to post the configuration to one of the Kafka Connect workers. Change http://localhost:8083/ the endpoint of one of your Kafka Connect worker(s).

Run the connector with this configuration.

curl -X POST -d @omnisci-sink-connector.json http://localhost:8083/connectors -H "Content-Type: application/json"

Next, create a record in the orders topic

bin/kafka-avro-console-producer \
 --broker-list localhost:9092 --topic orders \
 --property value.schema='{"type":"record","name":"myrecord","fields":[{"name":"id","type":"int"},{"name":"product", "type": "string"}, {"name":"quantity", "type": "int"}, {"name":"price",
 "type": "float"}]}'

The console producer is waiting for input. Copy and paste the following record into the terminal:

{"id": 999, "product": "foo", "quantity": 100, "price": 50}

To verify the data in HEAVY-AI, log in to the Docker container using the following command:

docker exec -it <containerid> bash


To find the container id, you can run the following command

docker ps

Once you are inside the Docker container, launch omnisql:


When prompted for a password, enter HyperInteractive.

Finally, run the following SQL query to verify the records:

omnisql> select * from orders;

HEAVY-AI Supported Versions

HEAVY-AI versions 4.5.0 and above are supported.

Data mapping

The sink connector requires knowledge of schemas, so you should use a suitable converter like the Avro converter that comes with Schema Registry or the JSON converter with schemas enabled. Kafka record keys (if present) can be primitive types or a Connect struct. The record value must be a Connect struct. Fields being selected from Connect structs must be primitive types. If the data in the topic is not of a compatible format, implementing a custom Converter may be necessary.

Auto-creation and Auto-evolution


Ensure the HEAVY-AI user has the appropriate permissions for DDL.

If auto.create is enabled, the connector can CREATE the destination table if it is found to be missing. The creation takes place online with records being consumed from the topic, since the connector uses the record schema as a basis for the table definition.

Note that HEAVY-AI does not support default values for columns. If your schema has fields with default values, they are added but the default value is ignored.

If auto.evolve is enabled, the connector can perform limited auto-evolution by issuing ALTER on the destination table when it encounters a record for which a column is found to be missing.

Since data type changes and removal of columns can be dangerous, the connector does not attempt to perform such evolutions on the table. Addition of primary key constraints is also not attempted.


For backward-compatible table schema evolution, new fields in record schemas must be optional. Mandatory fields, with or without a default value, are NOT supported. If you need to delete a field, the table schema should be manually altered to drop the corresponding column. Marking the column nullable does not work. You must drop the corresponding column.