Databricks
A unified analytics platform that brings together data engineering, science, and ML on a lakehouse architecture.
Overview
Databricks is a unified analytics platform built on Apache Spark, combining data engineering, machine learning, and collaborative notebooks in a single lakehouse architecture. It helps data teams move from raw data to production models at scale.
The Databricks integration for Queue enables AI agents to query data, trigger jobs, and interact with your lakehouse — helping engineering and data teams automate pipelines, monitor models, and surface insights programmatically.
How it works
Queue provides prebuilt Databricks workflows that connect AI agents to your data pipelines and ML infrastructure.
Job Orchestration
Trigger and monitor Databricks jobs and workflows from AI agent actions, with automatic handling of failures and retries.
Data Querying
Allow agents to run SQL queries against your Delta Lake tables, retrieve results, and use them to drive downstream decisions and automations.
Model Monitoring
Track model performance, data drift, and pipeline health — triggering alerts or retraining workflows automatically when thresholds are breached.
Configure
Open the Queue dashboard and navigate to Integrations
Search for Databricks and select the integration
Enter your Databricks workspace URL and generate a personal access token
Select the clusters, jobs, and catalogs you want Queue to access
Configure job triggers, query permissions, and AI agent workflows for your lakehouse environment
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