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Azure Data Catalog

CData CLI for Azure Data Catalog: Context for faster AI-driven integration

Context is the multiplier—give AI the right inputs, and it writes better code and ships faster.

Tired of AI hallucinations and debugging? CData CLI connects your coding agent to your actual Azure Data Catalog schema—no guessing, no fixing, just working code.

Install CData CLI
Decorative Icon Azure Data Catalog Logo

Reliable results from the terminal—AI validates against your real Azure Data Catalog data model

Faster development, because your agent reads your actual Azure Data Catalog structure before writing a single line of code.

  • Schema-aware code generation: Your agent reads Azure Data Catalog's exact table structures, column types, and relationships
  • Validated SQL syntax: Queries run against live Azure Data Catalog data before they reach your application
  • CData driver compatibility: Generated queries and code work identically with the Azure Data Catalog JDBC, ADO.NET, ODBC, and Python connectors
  • Production-ready applications: From prototype to deployment without rewriting
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Context is everything: AI + CLI

Why pairing your agent with the CLI works better than letting it guess at your schema


Grounded in your real schema

Your agent works from what's actually in Azure Data Catalog.

  • The CLI returns real schema and data from Azure Data Catalog
  • No more inventing field names or calling with wrong parameters
  • Outputs are deterministic and testable

Works in real environments

You stay in control. The CLI runs where your code already runs.

  • Compatible with the CData Azure Data Catalog JDBC, ADO.NET, ODBC, and Python drivers
  • Supports enterprise auth, TLS, proxies, and OS differences
  • Runs locally for dev, CI, and production workflows

Impact from the first integration

The agent gets the query right the first time.

  • Faster time to first working integration
  • Fewer production surprises
  • Less time lost to configuration debugging
  • Fewer repetitive support questions

AI connects, explores, ships. You just direct.

Build with CData CLI. Deploy with CData drivers.


01
Connect

Connect to Azure Data Catalog from the command line

Provide:

  • An activated Azure Data Catalog driver, downloaded with cdatacli drivers download and licensed with cdatacli drivers activate
  • A named connection created with cdatacli connection create

Get:

  • Schema discovery from a live connection to your source
  • Standardized SQL and stored procedure access
  • An encrypted connection file your agent refers to by name, so credentials aren't repeated on every command
02
Explore

Explore and validate in Cursor, Claude Code, or GitHub Copilot

Provide:

  • Natural language queries
  • Prompts for application code requirements

Get:

  • Accurate queries based on live schema from the source, using cdatacli metadata tables and cdatacli metadata columns
  • Precise filtering and JOINs from real sample values
  • Keyword-filtered schema, so your agent pulls the slice it asked for instead of the whole catalog
  • Executable code for your data-driven applications
03
Deploy

Build integrations that survive production

  • Schema and syntax parity between the CLI and the CData drivers you run in production
  • Standardize integration patterns across services and teams 
# AI helped write this. No AI runs it.

import cdata.azuredatacatalog as cdata_azuredatacatalog

conn = cdata_azuredatacatalog.connect("User=...;Password=...")
cursor = conn.cursor()

cursor.execute("""
SELECT Id, Name, Industry, AnnualRevenue
FROM Account
WHERE AnnualRevenue > 1000000
ORDER BY AnnualRevenue DESC
""")

for row in cursor.fetchall():
process_account(row)

# Runs as scheduled job, cron, or service
# No LLM. No tokens. Just reliable execution.

Integrate with Azure Data Catalog faster with CData CLI

Build data-driven applications connected to Azure Data Catalog

Your Java, .NET, C/C++, Go, Node.js, PHP, or Python application can interact with Azure Data Catalog faster than ever before. The biggest challenges in data-driven application development were schema discovery and query tuning. Your agent can handle both.

Prototype complex queries before production

Test JOINs, filters, and aggregations in your AI coding environment. Validated queries for Azure Data Catalog integrate directly into your applications without modification.

Automate Azure Data Catalog ETL scripts for your data warehouse

Generate scripts that query, transform, and sync Azure Data Catalog data to your warehouse. Built-in support for incremental updates across data sources.

Ready to get started? Try AI coding with Azure Data Catalog today

No more guessing, start shipping!

Install CData CLI