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Docker Reference Deployment

This section provides a reference deployment using Docker Compose. The deployment includes additional steps to publish data to the database before querying it back.

This is aimed at developers who wish to develop APIs that can be ran against their data. kdb Insights supports several interfaces, including:

  1. C
  2. Java
  3. q
  4. Python


To run this deployment, ensure that you have Docker installed with the Docker Compose extension.

Additionally, ensure that you place your kdb license into the provided lic folder. Your license must have the appropriate feature flags for running kdb Insights.

If you do not have, credentials to access the KX Docker registry, a kdb license, or you are unsure if your license has the required feature flags, please contact


Log in to the KX download portal to download the bundle. The bundle contains the compose.yaml and .env files that include the relevant images to stand up the database service. To access these images you must log in a docker registry.

docker login -u <user> -p <password>


curl -L$version/kxi-db-$version.tar.gz -o kxi-db.tar.gz


To start the kdb Insights Database, run the following command:

tar -xvf kxi-db.tar.gz
cd kxi-db/
docker compose up

Running this command starts the kdb Insights Database with a collection of sample schemas included in the config/assembly.yaml configuration file. If you need to introduce additional schemas, add them to this configuration file.

If you are using a Linux-based operating system, create the data folder manually and adjust the permissions to ensure it is readable by the container.

mkdir -p data/logs/rt data/db
chmod -R 777 data

Publishing and Querying Data

Below are examples that demonstrate how developers can publish data using kdb Insights through its interfaces.


To publish data using Python, run the following command:

docker compose -f config/docker-clients/compose-publish.yaml up

To publish data using Java, run the following command:

docker compose -f config/docker-clients/compose-java-ingest.yaml up


To query data using Python, run the following command:

docker compose -f config/docker-clients/compose-query.yaml up

To query data using REST, make a POST request with the following:

curl -X POST -H 'Content-Type: application/json' http://localhost:8080/data -d '{"table":"taxi"}'

To query data using q-based queries, use the following:

q)h:hopen 5050  // the SG has a tcp port forwarded locally on this port