Integrating Kiro CLI with Databricks Data via CData CLI
Kiro CLI is a terminal-based AI coding agent from AWS designed to take you from prompt to production directly in the command line. It understands your codebase through advanced code intelligence and context management and can autonomously execute multi-step workflows, running multiple agents in parallel, automating CI/CD pipelines, and integrating with external tools and data sources through native MCP support. Its support for agent steering files, custom agents, and agent skills makes it well-suited for structured, tool-driven workflows, making it a natural fit for connecting to external data sources through CData CLI. By describing your data goals in plain language, Kiro CLI can handle the full setup process, from driver configuration and license activation to connection creation and query execution, without manual intervention at each step.
This article details step-by-step directions for how to connect Databricks data to Kiro CLI through CData CLI.
Prerequisites
- Kiro CLI installed
- CData CLI installed
- Access to Databricks
About Databricks Data Integration
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
- Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
- Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
- Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
- Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.
While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.
Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.
Getting Started
Step 1: Download the skill (one-time setup)
Always use CData CLI with the official skill.
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The official CData CLI Skill on GitHub can be downloaded using npx skills through the terminal:
npx skills add CDataSoftware/cli-skills
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Follow the prompts in the terminal to install for Kiro CLI.
Step 2: Set up the project directory
Create a project directory to contain all project files.
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Navigate to your desired directory in the terminal and start a session with the kiro-cli command.
Step 3: Establish the driver and connection
Describe what you want to accomplish in this session with the CLI and Databricks data.
I would like to build a command line app that connects to Databricks and checks for updates from Customers. Make sure to include data from important columns like City and CompanyName.
This prompt automatically loads the skill and kicks off the following process. You can also manually prompt the agent for each step below.
- Driver setup: Kiro CLI checks for an existing CData Databricks driver, or searches and downloads a new one:
cdatacli drivers list
cdatacli drivers search Databricks
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cdatacli drivers download --artifact-id <artifact-id>
- Activation: Activate the Databricks driver with a single command for a trial or full license:
cdatacli drivers activate Databricks --name "<name>" --email "<email>" --trial
cdatacli drivers activate Databricks --name "<name>" --email "<email>" --key "<product-key>"
- Establish Databricks connection: Check for existing Databricks connections or create a new one:
cdatacli connection list
cdatacli drivers activate Databricks --name "<name>" --email "<email>" --trial
- Create a Databricks skill (if applicable): CData provides driver instructions for popular sources that can be used to create a source specific skill to guide the agent through best practices for the driver.
- Run the following command and save the output to your skills directory, either at the project level or globally. (Note: If you receive a "No instructions available for Databricks" message, no driver instructions exist for this source. You can continue using the main driver skill.)
cdatacli drivers skill Databricks > ~/skills/cdata-Databricks/SKILL.md
Step 4: Query Databricks data
With the CData driver fully configured, your agent can now execute queries and write code against live Databricks data:
cdatacli query sql --connection <my_Databricks_connection> --sql <SELECT * FROM table>
Query Databricks data directly from your terminal with CData CLI
Kiro CLI and CData CLI together give your AI coding agent a direct path to live Databricks data without custom middleware, scheduled syncs, or manual setup at each step. Describe your goal, and the agent handles driver configuration, connection setup, and query execution from start to finish in the terminal.
Download the free CData CLI and start a free, 30-day trial of the CData JDBC Driver for Databricks today.