Home Providers Azure Databricks
Azure Databricks
Azure Databricks is an Apache Spark-based analytics platform optimized for Microsoft Azure. It provides a collaborative workspace for data engineers, data scientists, and analysts to work together on big data and machine learning workloads.
Azure Databricks publishes 4 APIs on the APIs.io network, including REST API, Clusters API, Jobs API, and 1 more. Tagged areas include Analytics, Apache Spark, Big Data, Data Engineering, and Machine Learning.
The Azure Databricks catalog on APIs.io includes 1 JSON-LD context and 3 Spectral governance rulesets.
Azure Databricks’ developer surface includes authentication, getting-started guide, pricing, CLI, API reference, release notes, changelog, and 42 more developer resources.
39 APIs12 Features8 Use Cases
Analytics Apache Spark Big Data Data Engineering Machine Learning
On this page
Kin Score
APIs 39
Postman 1
Open Collections 1
Arazzo 20
Pricing Plans 2
Rate Limits 2
FinOps 2
Features 12
Vocabularies 1
Spectral Rules 3
JSON Schema 45
JSON Structure 23
Examples 54
Security Posture 3
Scopes 2
Agentic Access 1
Use Cases 8
Integrations 8
Resources 49
apis.yml
74 Operational Transparency
Composite quality — 56.5/100 · strong
Contract Quality 14.5 / 25
Developer Ergonomics 12.2 / 20
Commercial Clarity 10.0 / 20
Operational Transparency 9.6 / 13
Agent readiness — 31/100 · agent aware
18 / 18
10 / 10
0 / 12
10 / 10
0 / 9
0 / 8
0 / 7
7 / 7
0 / 6
0 / 5
0 / 4
0 / 3
0 / 8
0 / 4
Individual APIs this provider publishes, each with its own machine-readable definition.
Core REST API for managing Azure Databricks workspaces, clusters, jobs, notebooks, and other resources programmatically.
Manage Databricks clusters for running Spark jobs including creating, starting, editing, listing, terminating, and deleting clusters.
Create, manage, and run jobs on Databricks clusters including scheduling, listing runs, and managing job permissions.
Manage notebooks, folders, and other workspace objects including listing, importing, exporting, and deleting workspace items.
Access Databricks File System (DBFS) for file operations including uploading, downloading, listing, and deleting files and directories.
Manage libraries and dependencies on clusters including installing, uninstalling, and listing library statuses.
Manage secrets and secret scopes for secure credential storage including creating scopes, putting secrets, and managing ACLs.
Create and manage personal access tokens for API authentication including creating, listing, and revoking tokens.
Manage SQL warehouses, queries, and dashboards for Databricks SQL analytics workloads.
Track experiments, log metrics, and manage ML models using the MLflow tracking and registry APIs.
Create and manage instance pools to reduce cluster start and autoscaling times by maintaining a set of idle ready-to-use cloud instances.
Create, list, and edit cluster policies to control cluster configurations and limit the ability to configure clusters based on a set of rules.
Manage Git repositories within Databricks workspaces for version control of notebooks and files.
Manage Git credentials for authenticating with Git providers when using Databricks Repos.
Create, edit, delete, start, and view details about Delta Live Tables pipelines for building reliable data pipelines.
Manage permissions on workspace objects including clusters, jobs, notebooks, and other resources using access control lists.
Manage Unity Catalog catalogs for organizing and governing data assets across workspaces.
Manage schemas within Unity Catalog catalogs for organizing tables, views, and functions.
Manage tables within Unity Catalog schemas including listing, getting, and deleting tables.
Manage Unity Catalog volumes for governing non-tabular data such as files and directories.
Manage permissions and grants on Unity Catalog objects including catalogs, schemas, tables, and other securable objects.
Manage external locations in Unity Catalog for connecting to cloud storage paths.
Manage storage credentials in Unity Catalog for authenticating access to cloud storage.
Manage Unity Catalog metastores which serve as the top-level container for data governance.
Create and manage model serving endpoints for deploying machine learning models as REST API endpoints.
Manage registered models and model versions in the Databricks Model Registry for model lifecycle management.
Manage registered models in Unity Catalog for centralized model governance and sharing.
Manage global cluster initialization scripts that run on every cluster in the workspace.
Manage IP access lists to control network access to Azure Databricks workspaces.
Execute SQL statements on SQL warehouses and retrieve results for programmatic SQL access.
Execute commands on running clusters and retrieve results programmatically.
Manage files in Unity Catalog volumes and workspace filesystem with operations for uploading, downloading, and deleting files.
Deploy and manage Databricks Apps including creating, starting, stopping, and listing custom applications.
Manage Lakeview dashboards programmatically including creating, updating, and publishing dashboards.
Manage online tables for low-latency serving of feature data in Unity Catalog.
Manage vector search indexes for similarity search and retrieval-augmented generation workloads.
Manage vector search endpoints for hosting vector search indexes.
Retrieve query history for SQL warehouses including query text, status, and performance metrics.
Manage users, groups, and service principals across the Databricks account using SCIM 2.0 protocol.
Scroll for all 39
Ready-to-run Postman collections for exercising this provider's APIs.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Multi-step API workflows described with the Arazzo specification.
Scroll for all 20
Published pricing tiers and plan structures.
Documented rate limits and quota policies.
Cost, billing, and metering signals for API financial operations.
Notable capabilities this provider offers.
Scroll for all 12
JSON-LD contexts and semantic vocabularies used across these APIs.
Spectral governance rulesets for linting and validating these APIs.
Standalone JSON Schema definitions for this provider's data models.
Scroll for all 45
JSON Structure definitions describing this provider's data shapes.
Scroll for all 23
Example request and response payloads for these APIs.
Scroll for all 54
Authentication, domain security, vulnerability disclosure, and trust-center signals.
OAuth scopes governing access to this provider's APIs.
Recommended x-agentic-access execution contracts for AI agents.
What developers build with this provider.
Scroll for all 8
Pre-built integrations with other platforms and tools.
Scroll for all 8
Get Started 1
Portal, sign-up, and the first successful call
Documentation 3
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 23
Pagination, idempotency, versioning, errors, and events
Scroll for all 23
Build 8
SDKs, sample code, and the tooling you integrate with
Scroll for all 8
Access & Security 6
Authentication, authorization, and security posture
Operate 4
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Source (apis.yml)
name: Azure Databricks
description: Azure Databricks is an Apache Spark-based analytics platform optimized for Microsoft Azure. It provides a collaborative
workspace for data engineers, data scientists, and analysts to work together on big data and machine learning workloads.
image: https://azure.microsoft.com/svghandler/databricks/
tags:
- Analytics
- Apache Spark
- Big Data
- Data Engineering
- Machine Learning
created: '2024-01-01'
modified: '2026-05-19'
url: https://raw.githubusercontent.com/api-evangelist/azure-databricks/refs/heads/main/apis.yml
specificationVersion: '0.19'
apis:
- name: Azure Databricks REST API
description: Core REST API for managing Azure Databricks workspaces, clusters, jobs, notebooks, and other resources programmatically.
image: https://azure.microsoft.com/svghandler/databricks/
humanURL: https://learn.microsoft.com/azure/databricks/
baseURL: https://<databricks-instance>.azuredatabricks.net/api
tags:
- Clusters
- Jobs
- Notebooks
- Workspace
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/
- type: OpenAPI
url: openapi/azure-databricks-openapi.yml
- type: Authentication
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/authentication
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/introduction
- type: JSONSchema
url: json-schema/azure-databricks-cluster-schema.json
- type: JSONLD
url: json-ld/azure-databricks-context.jsonld
contact:
- type: Support
url: https://learn.microsoft.com/answers/tags/166/azure-databricks
- name: Clusters API
description: Manage Databricks clusters for running Spark jobs including creating, starting, editing, listing, terminating,
and deleting clusters.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/clusters
tags:
- Clusters
- Compute
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/clusters
- type: OpenAPI
url: openapi/azure-databricks-openapi.yml
- type: JSONSchema
url: json-schema/azure-databricks-cluster-schema.json
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/clusters
- name: Jobs API
description: Create, manage, and run jobs on Databricks clusters including scheduling, listing runs, and managing job permissions.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/jobs
tags:
- Automation
- Jobs
- Scheduling
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/jobs
- type: OpenAPI
url: openapi/azure-databricks-openapi.yml
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/jobs
- name: Workspace API
description: Manage notebooks, folders, and other workspace objects including listing, importing, exporting, and deleting
workspace items.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/workspace
tags:
- Folders
- Notebooks
- Workspace
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/workspace
- type: OpenAPI
url: openapi/azure-databricks-openapi.yml
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/workspace
- name: DBFS API
description: Access Databricks File System (DBFS) for file operations including uploading, downloading, listing, and deleting
files and directories.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/dbfs
tags:
- Files
- Storage
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/dbfs
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/dbfs
- name: Libraries API
description: Manage libraries and dependencies on clusters including installing, uninstalling, and listing library statuses.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/libraries
tags:
- Dependencies
- Libraries
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/libraries
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/libraries
- name: Secrets API
description: Manage secrets and secret scopes for secure credential storage including creating scopes, putting secrets,
and managing ACLs.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/secrets
tags:
- Credentials
- Secrets
- Security
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/secrets
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/secrets
- name: Token Management API
description: Create and manage personal access tokens for API authentication including creating, listing, and revoking tokens.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/token
tags:
- Authentication
- Security
- Tokens
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/token-management
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/tokenmanagement
- name: SQL Analytics API
description: Manage SQL warehouses, queries, and dashboards for Databricks SQL analytics workloads.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/sql
tags:
- Analytics
- Queries
- Sql
- Warehouses
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/sql/api/
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/warehouses
- name: MLflow API
description: Track experiments, log metrics, and manage ML models using the MLflow tracking and registry APIs.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/mlflow
tags:
- Experiments
- Machine Learning
- Mlops
- Model Tracking
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/mlflow/
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/experiments
- name: Instance Pools API
description: Create and manage instance pools to reduce cluster start and autoscaling times by maintaining a set of idle
ready-to-use cloud instances.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/instance-pools
tags:
- Clusters
- Compute
- Instance Pools
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/compute/pool-index
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/instancepools
- name: Cluster Policies API
description: Create, list, and edit cluster policies to control cluster configurations and limit the ability to configure
clusters based on a set of rules.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/policies/clusters
tags:
- Clusters
- Governance
- Policies
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/admin/clusters/policy-definition
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/clusterpolicies
- name: Repos API
description: Manage Git repositories within Databricks workspaces for version control of notebooks and files.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/repos
tags:
- Git
- Repositories
- Version Control
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/repos/
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/repos
- name: Git Credentials API
description: Manage Git credentials for authenticating with Git providers when using Databricks Repos.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/git-credentials
tags:
- Authentication
- Credentials
- Git
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/gitcredentials
- name: Pipelines API
description: Create, edit, delete, start, and view details about Delta Live Tables pipelines for building reliable data
pipelines.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/pipelines
tags:
- Data Engineering
- Delta Live Tables
- ETL
- Pipelines
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/ldp/
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/pipelines
- name: Permissions API
description: Manage permissions on workspace objects including clusters, jobs, notebooks, and other resources using access
control lists.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/permissions
tags:
- Access Control
- Permissions
- Security
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/security/auth/access-control/
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/permissions
- name: Unity Catalog - Catalogs API
description: Manage Unity Catalog catalogs for organizing and governing data assets across workspaces.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/catalogs
tags:
- Catalogs
- Data Governance
- Unity Catalog
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/data-governance/unity-catalog/
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/catalogs
- name: Unity Catalog - Schemas API
description: Manage schemas within Unity Catalog catalogs for organizing tables, views, and functions.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/schemas
tags:
- Data Governance
- Schemas
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/schemas
- name: Unity Catalog - Tables API
description: Manage tables within Unity Catalog schemas including listing, getting, and deleting tables.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/tables
tags:
- Data Governance
- Tables
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/tables
- name: Unity Catalog - Volumes API
description: Manage Unity Catalog volumes for governing non-tabular data such as files and directories.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/volumes
tags:
- Storage
- Unity Catalog
- Volumes
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/volumes
- name: Unity Catalog - Grants API
description: Manage permissions and grants on Unity Catalog objects including catalogs, schemas, tables, and other securable
objects.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/permissions
tags:
- Data Governance
- Permissions
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/grants
- name: Unity Catalog - External Locations API
description: Manage external locations in Unity Catalog for connecting to cloud storage paths.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/external-locations
tags:
- External Locations
- Storage
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/externallocations
- name: Unity Catalog - Storage Credentials API
description: Manage storage credentials in Unity Catalog for authenticating access to cloud storage.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/storage-credentials
tags:
- Credentials
- Security
- Storage
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/storagecredentials
- name: Unity Catalog - Metastores API
description: Manage Unity Catalog metastores which serve as the top-level container for data governance.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/metastores
tags:
- Data Governance
- Metastores
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/metastores
- name: Model Serving Endpoints API
description: Create and manage model serving endpoints for deploying machine learning models as REST API endpoints.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/serving-endpoints
tags:
- Deployment
- Inference
- Machine Learning
- Model Serving
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/machine-learning/model-serving/create-manage-serving-endpoints
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/servingendpoints
- name: Model Registry API
description: Manage registered models and model versions in the Databricks Model Registry for model lifecycle management.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/mlflow/databricks
tags:
- Machine Learning
- Mlops
- Model Registry
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/modelregistry
- name: Registered Models API
description: Manage registered models in Unity Catalog for centralized model governance and sharing.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.1/unity-catalog/models
tags:
- Machine Learning
- Model Registry
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/registeredmodels
- name: Global Init Scripts API
description: Manage global cluster initialization scripts that run on every cluster in the workspace.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/global-init-scripts
tags:
- Administration
- Clusters
- Initialization
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/globalinitscripts
- name: IP Access Lists API
description: Manage IP access lists to control network access to Azure Databricks workspaces.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/ip-access-lists
tags:
- Access Control
- Networking
- Security
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/ipaccesslists
- name: Statement Execution API
description: Execute SQL statements on SQL warehouses and retrieve results for programmatic SQL access.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/sql/statements
tags:
- Query Execution
- Sql
- Warehouses
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/statementexecution
- name: Command Execution API
description: Execute commands on running clusters and retrieve results programmatically.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/1.2
tags:
- Clusters
- Commands
- Execution
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/commandexecution
- name: Files API
description: Manage files in Unity Catalog volumes and workspace filesystem with operations for uploading, downloading,
and deleting files.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/fs/files
tags:
- Files
- Storage
- Unity Catalog
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/files
- name: Apps API
description: Deploy and manage Databricks Apps including creating, starting, stopping, and listing custom applications.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/apps
tags:
- Applications
- Deployment
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/apps
- name: Lakeview API
description: Manage Lakeview dashboards programmatically including creating, updating, and publishing dashboards.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/lakeview
tags:
- Dashboards
- Lakeview
- Visualization
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/lakeview
- name: Online Tables API
description: Manage online tables for low-latency serving of feature data in Unity Catalog.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/online-tables
tags:
- Feature Serving
- Machine Learning
- Online Tables
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/onlinetables
- name: Vector Search Indexes API
description: Manage vector search indexes for similarity search and retrieval-augmented generation workloads.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/vector-search/indexes
tags:
- AI
- RAG
- Similarity Search
- Vector Search
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/vectorsearchindexes
- name: Vector Search Endpoints API
description: Manage vector search endpoints for hosting vector search indexes.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/vector-search/endpoints
tags:
- AI
- Endpoints
- Vector Search
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/vectorsearchendpoints
- name: Query History API
description: Retrieve query history for SQL warehouses including query text, status, and performance metrics.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/sql/history/queries
tags:
- Monitoring
- Query History
- Sql
properties:
- type: APIReference
url: https://docs.databricks.com/api/azure/workspace/queryhistory
- name: Account SCIM API
description: Manage users, groups, and service principals across the Databricks account using SCIM 2.0 protocol.
baseURL: https://<databricks-instance>.azuredatabricks.net/api/2.0/account/scim/v2
tags:
- Groups
- Identity Management
- SCIM
- Users
properties:
- type: Documentation
url: https://learn.microsoft.com/azure/databricks/reference/scim-2-1
- type: APIReference
url: https://learn.microsoft.com/azure/databricks/dev-tools/api/latest/scim/scim-groups
common:
- type: AgenticAccess
url: agentic-access/microsoft-azure-databricks-agentic-access.yml
- type: VulnerabilityDisclosure
url: security/azure-databricks-vulnerability-disclosure.yml
- type: DomainSecurity
url: security/azure-databricks-domain-security.yml
- type: Authentication
url: authentication/azure-databricks-authentication.yml
- type: OAuthScopes
url: scopes/microsoft-azure-databricks-scopes.yml
- type: PostmanWorkspace
url: https://www.postman.com/kinlaneapi/azure-databricks/overview
- type: Arazzo
url: arazzo/azure-databricks-backup-notebook-workflow.yml
name: Azure Databricks Back Up a Notebook by Export and Re-import
- type: Arazzo
url: arazzo/azure-databricks-cancel-active-run-workflow.yml
name: Azure Databricks Cancel an Active Job Run
- type: Arazzo
url: arazzo/azure-databricks-cleanup-latest-job-run-workflow.yml
name: Azure Databricks Clean Up the Latest Completed Job Run
- type: Arazzo
url: arazzo/azure-databricks-cluster-health-diagnostics-workflow.yml
name: Azure Databricks Cluster Health Diagnostics
- type: Arazzo
url: arazzo/azure-databricks-create-directory-and-import-notebook-workflow.yml
name: Azure Databricks Create a Directory and Import a Notebook
- type: Arazzo
url: arazzo/azure-databricks-create-job-and-run-workflow.yml
name: Azure Databricks Create a Job and Run It to Completion
- type: Arazzo
url: arazzo/azure-databricks-delete-workspace-directory-workflow.yml
name: Azure Databricks Safely Delete a Workspace Directory
- type: Arazzo
url: arazzo/azure-databricks-import-notebook-and-run-workflow.yml
name: Azure Databricks Import a Notebook and Run It
- type: Arazzo
url: arazzo/azure-databricks-pin-most-recent-cluster-workflow.yml
name: Azure Databricks Pin the First Listed Cluster
- type: Arazzo
url: arazzo/azure-databricks-preflight-create-cluster-workflow.yml
name: Azure Databricks Preflight and Create a Cluster
- type: Arazzo
url: arazzo/azure-databricks-provision-cluster-and-run-job-workflow.yml
name: Azure Databricks Provision a Cluster and Run a Job on It
- type: Arazzo
url: arazzo/azure-databricks-provision-cluster-workflow.yml
name: Azure Databricks Provision and Wait for Cluster
- type: Arazzo
url: arazzo/azure-databricks-reset-job-and-verify-workflow.yml
name: Azure Databricks Overwrite Job Settings and Verify
- type: Arazzo
url: arazzo/azure-databricks-resize-running-cluster-workflow.yml
name: Azure Databricks Resize a Running Cluster and Wait
- type: Arazzo
url: arazzo/azure-databricks-restart-cluster-and-wait-workflow.yml
name: Azure Databricks Restart a Running Cluster and Wait
- type: Arazzo
url: arazzo/azure-databricks-run-existing-job-and-wait-workflow.yml
name: Azure Databricks Run an Existing Job and Wait
- type: Arazzo
url: arazzo/azure-databricks-start-cluster-and-wait-workflow.yml
name: Azure Databricks Start a Terminated Cluster and Wait
- type: Arazzo
url: arazzo/azure-databricks-submit-one-time-run-workflow.yml
name: Azure Databricks Submit a One-time Run and Wait
- type: Arazzo
url: arazzo/azure-databricks-terminate-and-purge-cluster-workflow.yml
name: Azure Databricks Terminate and Permanently Delete a Cluster
- type: Arazzo
url: arazzo/azure-databricks-update-job-and-rerun-workflow.yml
name: Azure Databricks Update a Job and Re-run It
- type: GettingStarted
url: https://learn.microsoft.com/azure/databricks/getting-started/
- type: Pricing
url: https://azure.microsoft.com/pricing/details/databricks/
- type: StatusPage
url: https://status.azuredatabricks.net/
- type: Security
url: https://learn.microsoft.com/azure/databricks/security/
- type: SDKs
url: https://learn.microsoft.com/azure/databricks/dev-tools/
- type: CLI
url: https://learn.microsoft.com/azure/databricks/dev-tools/cli/
- type: Authentication
url: https://learn.microsoft.com/azure/databricks/dev-tools/auth/
- type: APIReference
url: https://learn.microsoft.com/azure/databricks/reference/api
- type: ReleaseNotes
url: https://learn.microsoft.com/azure/databricks/release-notes/product/
- type: ChangeLog
url: https://learn.microsoft.com/azure/databricks/release-notes/
- type: Support
url: https://learn.microsoft.com/answers/tags/166/azure-databricks
- type: SDKs
url: https://learn.microsoft.com/azure/databricks/dev-tools/sdk-python
title: Python SDK
- type: SDKs
url: https://learn.microsoft.com/azure/databricks/dev-tools/sdk-java
title: Java SDK
- type: SDKs
url: https://learn.microsoft.com/azure/databricks/dev-tools/sdk-go
title: Go SDK
- type: SDKs
url: https://learn.microsoft.com/azure/databricks/dev-tools/sdk-r
title: R SDK
- type: GitHubRepository
url: https://github.com/Azure/azure-databricks-client
- type: OpenAPI
url: openapi/azure-databricks-openapi.yml
- type: JSONSchema
url: json-schema/azure-databricks-cluster-schema.json
- type: JSONLD
url: json-ld/azure-databricks-context.jsonld
- type: SpectralRules
url: rules/azure-databricks-spectral-rules.yml
- type: Vocabulary
url: vocabulary/azure-databricks-vocabulary.yaml
- type: Features
data:
- Collaborative notebooks with multi-language support
- Auto-scaling Apache Spark clusters
- Delta Lake for reliable data lakehouse architecture
- Unity Catalog for unified data governance
- MLflow integration for ML lifecycle management
- Model serving endpoints for real-time inference
- Delta Live Tables for declarative ETL pipelines
- SQL analytics with serverless SQL warehouses
- Vector search for RAG and similarity search
- Lakeview dashboards for data visualization
- Git integration for version control of notebooks
- SCIM 2.0 for identity and access management
- type: UseCases
data:
- Building and managing data lakehouse architectures
- Training and deploying machine learning models at scale
- Running ETL pipelines for data transformation
- Interactive data exploration and ad-hoc analytics
- Real-time streaming analytics with Structured Streaming
- Building retrieval-augmented generation (RAG) applications
- Data governance and compliance with Unity Catalog
- Collaborative data science with shared notebooks
- type: Integrations
data:
- Azure Data Factory for orchestration
- Azure Synapse Analytics for data warehousing
- Azure Data Lake Storage for scalable storage
- Azure Key Vault for secret management
- Azure Active Directory for authentication
- Power BI for business intelligence dashboards
- Terraform for infrastructure as code
- Apache Kafka for streaming data ingestion
- type: LlmsText
url: https://docs.databricks.com/llms.txt
- url: https://www.databricks.com/feed
type: Blog
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
- url: https://www.databricks.com/feed
type: Blog
Kin Score
How this is scored →