Databricks

aid: databricks
url: https://raw.githubusercontent.com/api-evangelist/databricks/refs/heads/main/apis.yml
apis:
  - aid: databricks:databricks
    name: Databricks
    tags:
      - Analytics
      - Data
      - Visualize
    humanURL: ' https://www.databricks.com'
    properties:
      - url: ' https://www.databricks.com'
        type: Documentation
      - url: https://docs.databricks.com/api/workspace/introduction
        type: APIReference
    description: >-
      Databricks is a cloud-based data platform that simplifies and accelerates the process of preparing and analyzing
      large volumes of data. The platform integrates with popular data sources and tools, allowing data engineers and
      data scientists to collaborate and work more efficiently. Databricks offers powerful features such as data
      visualization, machine learning, and real-time analytics, helping organizations make data-driven decisions and
      improve their business outcomes.
  - aid: databricks:clusters-api
    name: Databricks Clusters API
    tags:
      - Clusters
      - Compute
      - Infrastructure
    humanURL: https://docs.databricks.com/api/workspace/clusters
    properties:
      - url: https://docs.databricks.com/api/workspace/clusters
        type: Documentation
      - url: openapi/databricks-openapi.yml
        type: OpenAPI
      - url: json-schema/databricks-cluster-schema.json
        type: JSONSchema
      - url: json-schema/databricks-create-cluster-request-schema.json
        type: JSONSchema
      - url: json-schema/databricks-edit-cluster-request-schema.json
        type: JSONSchema
      - url: json-schema/databricks-cluster-details-schema.json
        type: JSONSchema
      - url: json-schema/databricks-spark-node-schema.json
        type: JSONSchema
      - url: json-schema/databricks-auto-scale-schema.json
        type: JSONSchema
      - url: json-schema/databricks-aws-attributes-schema.json
        type: JSONSchema
      - url: json-schema/databricks-azure-attributes-schema.json
        type: JSONSchema
      - url: json-schema/databricks-gcp-attributes-schema.json
        type: JSONSchema
      - url: json-schema/databricks-init-script-info-schema.json
        type: JSONSchema
      - url: json-schema/databricks-cluster-event-schema.json
        type: JSONSchema
      - url: json-schema/databricks-error-response-schema.json
        type: JSONSchema
      - url: json-ld/databricks-context.jsonld
        type: JSONLD
    description: >-
      The Databricks Clusters API allows you to create, start, edit, list, terminate, and delete clusters. Clusters are
      managed cloud resources that enable you to run data engineering and data science workloads on Apache Spark in the
      cloud. The API provides programmatic control over cluster lifecycle management, configuration, and monitoring.
  - aid: databricks:jobs-api
    name: Databricks Jobs API
    tags:
      - Jobs
      - Orchestration
      - Scheduling
      - Workflows
    humanURL: https://docs.databricks.com/api/workspace/jobs
    properties:
      - url: https://docs.databricks.com/api/workspace/jobs
        type: Documentation
      - url: openapi/databricks-openapi.yml
        type: OpenAPI
      - url: json-schema/databricks-job-schema.json
        type: JSONSchema
      - url: json-schema/databricks-create-job-request-schema.json
        type: JSONSchema
      - url: json-schema/databricks-task-settings-schema.json
        type: JSONSchema
      - url: json-schema/databricks-job-cluster-schema.json
        type: JSONSchema
      - url: json-schema/databricks-job-email-notifications-schema.json
        type: JSONSchema
      - url: json-schema/databricks-webhook-notifications-schema.json
        type: JSONSchema
      - url: json-schema/databricks-cron-schedule-schema.json
        type: JSONSchema
      - url: json-schema/databricks-git-source-schema.json
        type: JSONSchema
      - url: json-schema/databricks-library-schema.json
        type: JSONSchema
      - url: json-schema/databricks-access-control-request-schema.json
        type: JSONSchema
      - url: json-schema/databricks-job-settings-schema.json
        type: JSONSchema
      - url: json-schema/databricks-run-schema.json
        type: JSONSchema
      - url: json-schema/databricks-run-task-schema.json
        type: JSONSchema
      - url: json-ld/databricks-context.jsonld
        type: JSONLD
    description: >-
      The Databricks Jobs API allows you to create, edit, delete, and trigger jobs. Jobs are the primary mechanism for
      running automated workloads on Databricks, including notebooks, JARs, Python scripts, and Spark submit
      applications. The API supports complex multi-task workflows with dependencies, scheduling, and monitoring
      capabilities.
  - aid: databricks:dbfs-api
    name: Databricks DBFS API
    tags:
      - Data
      - Files
      - Storage
    humanURL: https://docs.databricks.com/api/workspace/dbfs
    properties:
      - url: https://docs.databricks.com/api/workspace/dbfs
        type: Documentation
    description: >-
      The Databricks File System (DBFS) API is a distributed file system mounted into a Databricks workspace and
      available on Databricks clusters. The API enables you to interact with object storage using directory and file
      semantics, allowing you to put, get, list, and delete files and directories programmatically.
  - aid: databricks:workspace-api
    name: Databricks Workspace API
    tags:
      - Folders
      - Notebooks
      - Workspace
    humanURL: https://docs.databricks.com/api/workspace/workspace
    properties:
      - url: https://docs.databricks.com/api/workspace/workspace
        type: Documentation
      - url: openapi/databricks-openapi.yml
        type: OpenAPI
      - url: json-schema/databricks-workspace-object-schema.json
        type: JSONSchema
      - url: json-ld/databricks-context.jsonld
        type: JSONLD
    description: >-
      The Databricks Workspace API allows you to list, import, export, and delete notebooks, folders, and libraries in a
      Databricks workspace. It provides programmatic access to manage workspace objects, enabling automation of notebook
      deployment and workspace organization.
  - aid: databricks:sql-warehouses-api
    name: Databricks SQL Warehouses API
    tags:
      - Analytics
      - SQL
      - Warehouses
    humanURL: https://docs.databricks.com/api/workspace/warehouses
    properties:
      - url: https://docs.databricks.com/api/workspace/warehouses
        type: Documentation
    description: >-
      The Databricks SQL Warehouses API allows you to create, edit, list, start, stop, and delete SQL warehouses. SQL
      warehouses are compute resources that enable you to run SQL commands on data objects within Databricks SQL,
      providing serverless or classic compute options for analytical workloads.
  - aid: databricks:pipelines-api
    name: Databricks Pipelines API
    tags:
      - Delta Live Tables
      - ETL
      - Pipelines
    humanURL: https://docs.databricks.com/api/workspace/pipelines
    properties:
      - url: https://docs.databricks.com/api/workspace/pipelines
        type: Documentation
    description: >-
      The Databricks Pipelines API allows you to create, edit, delete, start, and stop Delta Live Tables pipelines.
      Delta Live Tables is a declarative framework for building reliable, maintainable, and testable data processing
      pipelines. The API provides full lifecycle management of ETL pipelines.
  - aid: databricks:serving-endpoints-api
    name: Databricks Serving Endpoints API
    tags:
      - AI
      - Machine Learning
      - Model Serving
    humanURL: https://docs.databricks.com/api/workspace/servingendpoints
    properties:
      - url: https://docs.databricks.com/api/workspace/servingendpoints
        type: Documentation
    description: >-
      The Databricks Serving Endpoints API allows you to create, update, query, and delete model serving endpoints.
      Mosaic AI Model Serving provides a unified interface to deploy, govern, and query AI models, including custom
      models, generative AI models, and large language models, with high availability and low latency.
  - aid: databricks:secrets-api
    name: Databricks Secrets API
    tags:
      - Credentials
      - Secrets
      - Security
    humanURL: https://docs.databricks.com/api/workspace/secrets
    properties:
      - url: https://docs.databricks.com/api/workspace/secrets
        type: Documentation
    description: >-
      The Databricks Secrets API allows you to manage secrets, secret scopes, and secret ACLs. Secrets provide a secure
      way to store and reference credentials and other sensitive information in notebooks and jobs without exposing them
      in plaintext.
  - aid: databricks:instance-pools-api
    name: Databricks Instance Pools API
    tags:
      - Clusters
      - Compute
      - Infrastructure
    humanURL: https://docs.databricks.com/api/workspace/instancepools
    properties:
      - url: https://docs.databricks.com/api/workspace/instancepools
        type: Documentation
    description: >-
      The Databricks Instance Pools API allows you to create, edit, delete, and list instance pools. Instance pools
      reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use cloud instances, improving
      performance and reducing costs for frequently used cluster configurations.
  - aid: databricks:token-management-api
    name: Databricks Token Management API
    tags:
      - Authentication
      - Security
      - Tokens
    humanURL: https://docs.databricks.com/api/workspace/tokenmanagement
    properties:
      - url: https://docs.databricks.com/api/workspace/tokenmanagement
        type: Documentation
    description: >-
      The Databricks Token Management API enables workspace administrators to manage personal access tokens for users
      and service principals. It allows creating, listing, and revoking tokens, providing centralized control over API
      authentication credentials.
  - aid: databricks:catalogs-api
    name: Databricks Catalogs API
    tags:
      - Data Governance
      - Metadata
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/catalogs
    properties:
      - url: https://docs.databricks.com/api/workspace/catalogs
        type: Documentation
    description: >-
      The Databricks Catalogs API is part of Unity Catalog and allows you to create, update, list, and delete catalogs.
      Catalogs are the top-level container for data objects in Unity Catalog, providing a three-level namespace
      (catalog.schema.table) for organizing and governing data assets across workspaces.
  - aid: databricks:vector-search-indexes-api
    name: Databricks Vector Search Indexes API
    tags:
      - AI
      - Embeddings
      - Vector Search
    humanURL: https://docs.databricks.com/api/workspace/vectorsearchindexes
    properties:
      - url: https://docs.databricks.com/api/workspace/vectorsearchindexes
        type: Documentation
    description: >-
      The Databricks Vector Search Indexes API allows you to create, manage, query, and delete vector search indexes.
      Vector Search enables you to store vector representations of your data and perform similarity searches, powering
      retrieval-augmented generation (RAG) applications and other AI use cases.
  - aid: databricks:model-versions-api
    name: Databricks Model Versions API
    tags:
      - Machine Learning
      - MLflow
      - Model Registry
    humanURL: https://docs.databricks.com/api/workspace/modelversions
    properties:
      - url: https://docs.databricks.com/api/workspace/modelversions
        type: Documentation
    description: >-
      The Databricks Model Versions API allows you to manage model versions within the Unity Catalog model registry. It
      provides programmatic access to create, update, list, and delete model versions, enabling automated ML lifecycle
      management and model governance.
  - aid: databricks:permissions-api
    name: Databricks Permissions API
    tags:
      - Access Control
      - Authorization
      - Security
    humanURL: https://docs.databricks.com/api/workspace/permissions
    properties:
      - url: https://docs.databricks.com/api/workspace/permissions
        type: Documentation
    description: >-
      The Databricks Permissions API allows you to manage permissions on workspace objects such as clusters, jobs,
      notebooks, and SQL warehouses. It provides programmatic access to get, set, and update access control lists for
      various Databricks resources, enabling fine-grained authorization management.
  - aid: databricks:repos-api
    name: Databricks Repos API
    tags:
      - Git
      - Repositories
      - Version Control
    humanURL: https://docs.databricks.com/api/workspace/repos
    properties:
      - url: https://docs.databricks.com/api/workspace/repos
        type: Documentation
    description: >-
      The Databricks Repos API allows you to manage Git repositories within a Databricks workspace. It provides
      programmatic access to create, update, delete, and list repos, as well as perform Git operations like pulling
      latest changes, enabling version-controlled notebook and code development.
  - aid: databricks:git-credentials-api
    name: Databricks Git Credentials API
    tags:
      - Authentication
      - Credentials
      - Git
    humanURL: https://docs.databricks.com/api/workspace/gitcredentials
    properties:
      - url: https://docs.databricks.com/api/workspace/gitcredentials
        type: Documentation
    description: >-
      The Databricks Git Credentials API allows you to manage Git credentials for authenticating with Git providers. It
      provides programmatic access to create, update, delete, and list stored Git credentials, enabling seamless
      integration with GitHub, GitLab, Bitbucket, and other Git hosting services.
  - aid: databricks:cluster-policies-api
    name: Databricks Cluster Policies API
    tags:
      - Clusters
      - Governance
      - Policies
    humanURL: https://docs.databricks.com/api/workspace/clusterpolicies
    properties:
      - url: https://docs.databricks.com/api/workspace/clusterpolicies
        type: Documentation
    description: >-
      The Databricks Cluster Policies API allows administrators to create, edit, delete, and list cluster policies.
      Cluster policies limit the ability to configure clusters based on a set of rules, enabling administrators to
      enforce cost controls and governance over compute resources.
  - aid: databricks:libraries-api
    name: Databricks Libraries API
    tags:
      - Clusters
      - Dependencies
      - Libraries
    humanURL: https://docs.databricks.com/api/workspace/libraries
    properties:
      - url: https://docs.databricks.com/api/workspace/libraries
        type: Documentation
    description: >-
      The Databricks Libraries API allows you to install, uninstall, and list libraries on clusters. It provides
      programmatic management of Python, Java, Scala, and R library dependencies for cluster workloads, enabling
      automated environment configuration.
  - aid: databricks:global-init-scripts-api
    name: Databricks Global Init Scripts API
    tags:
      - Administration
      - Compute
      - Configuration
    humanURL: https://docs.databricks.com/api/workspace/globalinitscripts
    properties:
      - url: https://docs.databricks.com/api/workspace/globalinitscripts
        type: Documentation
    description: >-
      The Databricks Global Init Scripts API enables workspace administrators to manage global initialization scripts
      that run on every cluster in the workspace. It provides programmatic access to create, update, delete, list, and
      reorder init scripts for consistent cluster configuration.
  - aid: databricks:command-execution-api
    name: Databricks Command Execution API
    tags:
      - Commands
      - Compute
      - Execution
    humanURL: https://docs.databricks.com/api/workspace/commandexecution
    properties:
      - url: https://docs.databricks.com/api/workspace/commandexecution
        type: Documentation
    description: >-
      The Databricks Command Execution API allows you to execute Python, Scala, SQL, or R commands on running Databricks
      clusters. It provides programmatic access to create execution contexts, run commands, check status, and retrieve
      results, enabling remote interactive cluster usage.
  - aid: databricks:statement-execution-api
    name: Databricks Statement Execution API
    tags:
      - Queries
      - SQL
      - Warehouses
    humanURL: https://docs.databricks.com/api/workspace/statementexecution
    properties:
      - url: https://docs.databricks.com/api/workspace/statementexecution
        type: Documentation
    description: >-
      The Databricks Statement Execution API allows you to execute SQL statements on Databricks SQL warehouses and
      retrieve results. It provides a synchronous and asynchronous interface for running SQL queries, checking execution
      status, fetching result data, and canceling statements.
  - aid: databricks:queries-api
    name: Databricks Queries API
    tags:
      - Analytics
      - Queries
      - SQL
    humanURL: https://docs.databricks.com/api/workspace/queries
    properties:
      - url: https://docs.databricks.com/api/workspace/queries
        type: Documentation
    description: >-
      The Databricks Queries API allows you to create, update, delete, list, and run saved SQL queries in Databricks
      SQL. It provides programmatic management of SQL query objects, enabling automation of analytical workflows and
      query lifecycle management.
  - aid: databricks:alerts-api
    name: Databricks Alerts API
    tags:
      - Alerts
      - Monitoring
      - SQL
    humanURL: https://docs.databricks.com/api/workspace/alerts
    properties:
      - url: https://docs.databricks.com/api/workspace/alerts
        type: Documentation
    description: >-
      The Databricks Alerts API allows you to create, update, delete, and list alerts in Databricks SQL. Alerts automate
      query execution, evaluate custom conditions, and deliver notifications when those conditions are met, enabling
      proactive monitoring of business data.
  - aid: databricks:schemas-api
    name: Databricks Schemas API
    tags:
      - Data Governance
      - Schemas
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/schemas
    properties:
      - url: https://docs.databricks.com/api/workspace/schemas
        type: Documentation
    description: >-
      The Databricks Schemas API is part of Unity Catalog and allows you to create, update, list, and delete schemas.
      Schemas, also known as databases, reside within catalogs and contain tables, views, volumes, functions, and
      models, providing the second level of the three-level namespace for data organization.
  - aid: databricks:tables-api
    name: Databricks Tables API
    tags:
      - Data Governance
      - Tables
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/tables
    properties:
      - url: https://docs.databricks.com/api/workspace/tables
        type: Documentation
    description: >-
      The Databricks Tables API is part of Unity Catalog and allows you to create, update, list, and delete tables.
      Tables reside within schemas and represent structured data assets, supporting managed and external table types
      with full governance and access control through Unity Catalog.
  - aid: databricks:volumes-api
    name: Databricks Volumes API
    tags:
      - Storage
      - Unity Catalog
      - Volumes
    humanURL: https://docs.databricks.com/api/workspace/volumes
    properties:
      - url: https://docs.databricks.com/api/workspace/volumes
        type: Documentation
    description: >-
      The Databricks Volumes API is part of Unity Catalog and allows you to create, update, list, and delete volumes.
      Volumes provide a governed location for storing and accessing non-tabular data files such as images, documents,
      and other unstructured data within the Unity Catalog namespace.
  - aid: databricks:functions-api
    name: Databricks Functions API
    tags:
      - Functions
      - SQL
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/functions
    properties:
      - url: https://docs.databricks.com/api/workspace/functions
        type: Documentation
    description: >-
      The Databricks Functions API is part of Unity Catalog and allows you to create, list, and delete user-defined
      functions. Functions reside within schemas and can be used in SQL queries and notebooks, with full governance and
      access control managed through Unity Catalog.
  - aid: databricks:grants-api
    name: Databricks Grants API
    tags:
      - Access Control
      - Security
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/grants
    properties:
      - url: https://docs.databricks.com/api/workspace/grants
        type: Documentation
    description: >-
      The Databricks Grants API is part of Unity Catalog and allows you to get, update, and manage permissions on Unity
      Catalog securable objects. It provides programmatic control over access to catalogs, schemas, tables, volumes, and
      other data assets, enabling fine-grained data governance.
  - aid: databricks:external-locations-api
    name: Databricks External Locations API
    tags:
      - Cloud Storage
      - Storage
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/externallocations
    properties:
      - url: https://docs.databricks.com/api/workspace/externallocations
        type: Documentation
    description: >-
      The Databricks External Locations API is part of Unity Catalog and allows you to create, update, list, and delete
      external locations. External locations combine a cloud storage path with a storage credential, enabling governed
      access to data stored in external cloud storage systems.
  - aid: databricks:storage-credentials-api
    name: Databricks Storage Credentials API
    tags:
      - Cloud Storage
      - Security
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/storagecredentials
    properties:
      - url: https://docs.databricks.com/api/workspace/storagecredentials
        type: Documentation
    description: >-
      The Databricks Storage Credentials API is part of Unity Catalog and allows you to create, update, list, and delete
      storage credentials. Storage credentials contain long-term cloud credentials that provide access to cloud storage,
      and are referenced when creating external locations for governing data access.
  - aid: databricks:metastores-api
    name: Databricks Metastores API
    tags:
      - Data Governance
      - Metadata
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/metastores
    properties:
      - url: https://docs.databricks.com/api/workspace/metastores
        type: Documentation
    description: >-
      The Databricks Metastores API is part of Unity Catalog and allows you to create, update, list, and delete
      metastores. A metastore is the top-level container of objects in Unity Catalog, providing centralized metadata
      management, access control, and data governance across workspaces.
  - aid: databricks:connections-api
    name: Databricks Connections API
    tags:
      - Connections
      - External Data
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/connections
    properties:
      - url: https://docs.databricks.com/api/workspace/connections
        type: Documentation
    description: >-
      The Databricks Connections API is part of Unity Catalog and allows you to create, update, list, and delete
      connections to external data sources. Connections enable federated queries across external databases and data
      systems, extending Unity Catalog governance to data outside the lakehouse.
  - aid: databricks:registered-models-api
    name: Databricks Registered Models API
    tags:
      - Machine Learning
      - MLflow
      - Model Registry
    humanURL: https://docs.databricks.com/api/workspace/registeredmodels
    properties:
      - url: https://docs.databricks.com/api/workspace/registeredmodels
        type: Documentation
    description: >-
      The Databricks Registered Models API allows you to create, update, list, and delete registered models in the Unity
      Catalog model registry. It provides centralized model lifecycle management with versioning, aliasing, and
      governance capabilities for machine learning models.
  - aid: databricks:experiments-api
    name: Databricks Experiments API
    tags:
      - Experiments
      - Machine Learning
      - MLflow
    humanURL: https://docs.databricks.com/api/workspace/experiments
    properties:
      - url: https://docs.databricks.com/api/workspace/experiments
        type: Documentation
    description: >-
      The Databricks Experiments API allows you to create, update, list, and manage MLflow experiments. Experiments are
      the primary unit of organization in MLflow, grouping runs that track parameters, metrics, and artifacts for
      machine learning model development and comparison.
  - aid: databricks:online-tables-api
    name: Databricks Online Tables API
    tags:
      - Feature Serving
      - Real-Time
      - Tables
    humanURL: https://docs.databricks.com/api/workspace/onlinetables
    properties:
      - url: https://docs.databricks.com/api/workspace/onlinetables
        type: Documentation
    description: >-
      The Databricks Online Tables API allows you to create, get, and delete online tables. Online tables are
      materialized copies of Delta tables optimized for low-latency lookups, enabling real-time feature serving and
      online inference workloads for machine learning applications.
  - aid: databricks:quality-monitors-api
    name: Databricks Quality Monitors API
    tags:
      - Data Quality
      - Monitoring
      - Observability
    humanURL: https://docs.databricks.com/api/workspace/qualitymonitors
    properties:
      - url: https://docs.databricks.com/api/workspace/qualitymonitors
        type: Documentation
    description: >-
      The Databricks Quality Monitors API allows you to create, update, get, and delete data quality monitors for
      tables. Quality monitors enable automated data profiling and anomaly detection, providing continuous monitoring of
      data quality metrics and statistical properties.
  - aid: databricks:vector-search-endpoints-api
    name: Databricks Vector Search Endpoints API
    tags:
      - AI
      - Compute
      - Vector Search
    humanURL: https://docs.databricks.com/api/workspace/vectorsearchendpoints
    properties:
      - url: https://docs.databricks.com/api/workspace/vectorsearchendpoints
        type: Documentation
    description: >-
      The Databricks Vector Search Endpoints API allows you to create, list, get, and delete vector search endpoints.
      Vector search endpoints are compute resources that host vector search indexes, enabling similarity search queries
      for retrieval-augmented generation and other AI applications.
  - aid: databricks:shares-api
    name: Databricks Shares API
    tags:
      - Collaboration
      - Data Sharing
      - Delta Sharing
    humanURL: https://docs.databricks.com/api/workspace/shares
    properties:
      - url: https://docs.databricks.com/api/workspace/shares
        type: Documentation
    description: >-
      The Databricks Shares API is part of Delta Sharing and allows you to create, update, list, and delete shares. A
      share is a read-only logical collection of tables and table partitions that a data provider wants to share with
      one or more recipients for secure cross-organization data sharing.
  - aid: databricks:recipients-api
    name: Databricks Recipients API
    tags:
      - Access Control
      - Data Sharing
      - Delta Sharing
    humanURL: https://docs.databricks.com/api/workspace/recipients
    properties:
      - url: https://docs.databricks.com/api/workspace/recipients
        type: Documentation
    description: >-
      The Databricks Recipients API is part of Delta Sharing and allows you to create, update, list, and delete
      recipients. A recipient is an entity that receives shared data from a provider, and can be either a Databricks
      workspace or an open-protocol recipient using bearer tokens.
  - aid: databricks:providers-api
    name: Databricks Providers API
    tags:
      - Data Sharing
      - Delta Sharing
      - Marketplace
    humanURL: https://docs.databricks.com/api/workspace/providers
    properties:
      - url: https://docs.databricks.com/api/workspace/providers
        type: Documentation
    description: >-
      The Databricks Providers API is part of Delta Sharing and allows you to create, update, list, and delete data
      providers. Providers represent organizations that share data through Delta Sharing, enabling secure and governed
      cross-organization data exchange.
  - aid: databricks:clean-rooms-api
    name: Databricks Clean Rooms API
    tags:
      - Clean Rooms
      - Collaboration
      - Privacy
    humanURL: https://docs.databricks.com/api/workspace/cleanrooms
    properties:
      - url: https://docs.databricks.com/api/workspace/cleanrooms
        type: Documentation
    description: >-
      The Databricks Clean Rooms API allows you to create, update, list, and delete clean rooms. Clean rooms use Delta
      Sharing and serverless compute to provide a secure and privacy-protecting environment where multiple parties can
      collaborate on sensitive enterprise data without exposing raw data.
  - aid: databricks:notification-destinations-api
    name: Databricks Notification Destinations API
    tags:
      - Alerts
      - Integration
      - Notifications
    humanURL: https://docs.databricks.com/api/workspace/notificationdestinations
    properties:
      - url: https://docs.databricks.com/api/workspace/notificationdestinations
        type: Documentation
    description: >-
      The Databricks Notification Destinations API allows you to create, update, list, and delete notification
      destinations for a workspace. Notification destinations define where alerts and notifications are sent, supporting
      integrations with email, Slack, PagerDuty, webhooks, and other channels.
  - aid: databricks:apps-api
    name: Databricks Apps API
    tags:
      - Applications
      - Deployment
      - Development
    humanURL: https://docs.databricks.com/api/workspace/apps
    properties:
      - url: https://docs.databricks.com/api/workspace/apps
        type: Documentation
    description: >-
      The Databricks Apps API allows you to create, deploy, manage, and delete Databricks Apps. Apps run directly on a
      Databricks workspace, integrating with workspace data and services to build custom data applications, dashboards,
      and tools with built-in authentication and authorization.
  - aid: databricks:lakeview-api
    name: Databricks Lakeview API
    tags:
      - Analytics
      - Dashboards
      - Visualization
    humanURL: https://docs.databricks.com/api/workspace/lakeview
    properties:
      - url: https://docs.databricks.com/api/workspace/lakeview
        type: Documentation
    description: >-
      The Databricks Lakeview API allows you to create, update, get, list, and delete AI/BI dashboards. Lakeview
      dashboards provide a modern visualization experience built on top of Databricks SQL, enabling interactive data
      exploration and business intelligence reporting.
  - aid: databricks:files-api
    name: Databricks Files API
    tags:
      - Files
      - Storage
      - Unity Catalog
    humanURL: https://docs.databricks.com/api/workspace/files
    properties:
      - url: https://docs.databricks.com/api/workspace/files
        type: Documentation
    description: >-
      The Databricks Files API provides a standard HTTP interface for reading, writing, listing, and deleting files and
      directories in Unity Catalog volumes and other workspace storage locations. It supports direct file access by URI,
      enabling seamless file management for data and ML workloads.
  - aid: databricks:tokens-api
    name: Databricks Tokens API
    tags:
      - Authentication
      - Security
      - Tokens
    humanURL: https://d

# --- truncated at 32 KB (50 KB total) ---
# Full source: https://raw.githubusercontent.com/api-evangelist/databricks/refs/heads/main/apis.yml