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 - url: graphql/databricks-graphql.md type: GraphQL 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: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: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://docs.databricks.com/api/workspace/tokens properties: - url: https://docs.databricks.com/api/workspace/tokens type: Documentation description: >- The Databricks Tokens API allows you to create, list, and revoke personal access tokens. Personal access tokens are used to authenticate with the Databricks REST API and integrations, providing an alternative to OAuth for programmatic access. - aid: databricks:ip-access-lists-api name: Databricks IP Access Lists API tags: - Access Control - Networking - Security humanURL: https://docs.databricks.com/api/workspace/ipaccesslists properties: - url: https://docs.databricks.com/api/workspace/ipaccesslists type: Documentation description: >- The Databricks IP Access Lists API allows administrators to configure IP allow lists and block lists for a workspace. It provides programmatic management of network security rules to restrict access to the workspace based on IP addresses or CIDR ranges. - aid: databricks:current-user-api name: Databricks Current User API tags: - Authentication - Identity - Users humanURL: https://docs.databricks.com/api/workspace/currentuser properties: - url: https://docs.databricks.com/api/workspace/currentuser type: Documentation description: >- The Databricks Current User API allows you to retrieve information about the currently authenticated user or service principal. It returns identity details including username, display name, and group memberships for the caller making the API request. - aid: databricks:groups-api name: Databricks Groups API tags: - Access Control - Groups - Identity humanURL: https://docs.databricks.com/api/workspace/groups properties: - url: https://docs.databricks.com/api/workspace/groups type: Documentation description: >- The Databricks Groups API allows you to create, update, list, and delete groups in a workspace. Groups simplify identity management by enabling administrators to assign access permissions to collections of users and service principals rather than managing them individually. - aid: databricks:service-principals-api name: Databricks Service Principals API tags: - Automation - Identity - Service Principals humanURL: https://docs.databricks.com/api/workspace/serviceprincipals properties: - url: https://docs.databricks.com/api/workspace/serviceprincipals type: Documentation description: >- The Databricks Service Principals API allows you to create, update, list, and delete service principals in a workspace. Service principals are identities for automated tools, jobs, scripts, apps, and CI/CD platforms, enabling secure non-interactive authentication with Databricks resources. - aid: databricks:users-api name: Databricks Users API tags: - Administration - Identity - Users humanURL: https://docs.databricks.com/api/workspace/users properties: - url: https://docs.databricks.com/api/workspace/users type: Documentation description: >- The Databricks Users API allows you to create, update, list, and delete users in a workspace. It provides programmatic management of user identities and their workspace access, supporting SCIM protocol for identity provider integration and automated user provisioning. - aid: databricks:dashboards-api name: Databricks Dashboards API tags: - Dashboards - SQL - Visualization humanURL: https://docs.databricks.com/api/workspace/dashboards properties: - url: https://docs.databricks.com/api/workspace/dashboards type: Documentation description: >- The Databricks Dashboards API allows you to create, update, list, and delete legacy SQL dashboards. Dashboards provide visual representations of query results, enabling business intelligence reporting and data visualization directly within Databricks SQL. - aid: databricks:model-registry-api name: Databricks Model Registry API tags: - Machine Learning - MLflow - Model Registry humanURL: https://docs.databricks.com/api/workspace/modelregistry properties: - url: https://docs.databricks.com/api/workspace/modelregistry type: Documentation description: >- The Databricks Model Registry API provides the workspace model registry for managing the full lifecycle of ML models. It enables creating registered models, managing model versions, transitioning stages, and setting permissions for collaborative model governance and deployment. - aid: databricks:workspace-bindings-api name: Databricks Workspace Bindings API tags: - Governance - Unity Catalog - Workspace humanURL: https://docs.databricks.com/api/workspace/workspacebindings properties: - url: https://docs.databricks.com/api/workspace/workspacebindings type: Documentation description: >- The Databricks Workspace Bindings API allows you to manage the binding of Unity Catalog securables to specific workspaces. It enables configuring whether catalogs and other objects are available across all workspaces or isolated to specific ones, supporting multi-workspace governance. - aid: databricks:system-schemas-api name: Databricks System Schemas API tags: - Monitoring - System Tables - Unity Catalog humanURL: https://docs.databricks.com/api/workspace/systemschemas properties: - url: https://docs.databricks.com/api/workspace/systemschemas type: Documentation description: >- The Databricks System Schemas API allows you to enable, disable, and list system schemas within a metastore. System schemas contain system tables that provide operational data about your Databricks account, including audit logs, billing usage, lineage, and access history. - aid: databricks:table-constraints-api name: Databricks Table Constraints API tags: - Data Quality - Tables - Unity Catalog humanURL: https://docs.databricks.com/api/workspace/tableconstraints properties: - url: https://docs.databricks.com/api/workspace/tableconstraints type: Documentation description: >- The Databricks Table Constraints API allows you to create and delete primary key and foreign key constraints on Unity Catalog tables. Table constraints define relationships between tables, supporting data integrity and enabling query optimization across the lakehouse. - aid: databricks:databricks-clusters-api name: Databricks Clusters API description: >- Manage Databricks clusters for running data engineering and data science workloads on Apache Spark. humanURL: ' https://www.databricks.com' tags: - Clusters properties: - type: OpenAPI url: openapi/databricks-clusters-api-openapi.yml - type: Documentation url: https://docs.databricks.com/api/workspace/clusters - type: JSONSchema 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: JSONLD url: json-ld/databricks-context.jsonld - type: Documentation url: https://docs.databricks.com/api/workspace/jobs - type: JSONSchema 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: Documentation url: https://docs.databricks.com/api/workspace/workspace - type: JSONSchema url: json-schema/databricks-workspace-object-schema.json - aid: databricks:databricks-jobs-api name: Databricks Jobs API description: >- Create and manage automated workloads including notebooks, JARs, Python scripts, and multi-task workflows. humanURL: ' https://www.databricks.com' tags: - Jobs properties: - type: OpenAPI url: openapi/databricks-jobs-api-openapi.yml - type: Documentation url: https://docs.databricks.com/api/workspace/clusters - type: JSONSchema 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: JSONLD url: json-ld/databricks-context.jsonld - type: Documentation url: https://docs.databricks.com/api/workspace/jobs - type: JSONSchema 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: Documentation url: https://docs.databricks.com/api/workspace/workspace - type: JSONSchema url: json-schema/databricks-workspace-object-schema.json - aid: databricks:databricks-workspace-api name: Databricks Workspace API description: Manage workspace objects such as notebooks, folders, and libraries. humanURL: ' https://www.databricks.com' tags: - Workspace properties: - type: OpenAPI url: openapi/databricks-workspace-api-openapi.yml - type: Documentation url: https://docs.databricks.com/api/workspace/clusters - type: JSONSchema 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: JSONLD url: json-ld/databricks-context.jsonld - type: Documentation url: https://docs.databricks.com/api/workspace/jobs - type: JSONSchema 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: Documentation url: https://docs.databricks.com/api/workspace/workspace - type: JSONSchema url: json-schema/databricks-workspace-object-schema.json name: Databricks tags: - AI - Analytics - Apache Spark - Big Data - Clean Rooms - Cloud Computing - Data - Data Analytics - Data Engineering - Data Governance - Delta Lake - Delta Sharing - ETL - Identity Management - Lakehouse - Machine Learning - MLflow - Model Serving - Security - SQL - Unity Catalog - Vector Search - Visualize type: Index accessModel: pricing: paid onboarding: self-serve trial: false try_now: false public: false label: Paid ยท Self-serve signup confidence: high source: - plans - authentication generated: '2026-07-22' method: derived image: https://www.databricks.com/en-website-assets/static/f9f2b15ae456c41f7d2e5b303c8c6c6e/databricks-logo.svg access: 3rd-Party created: '2025-01-14' modified: '2026-05-19' position: Consumer description: Collection of Databricks REST APIs for managing workspaces, clusters, jobs, and data operations. integrations: - name: Databricks - name: Fivetran - name: Hevo Data - name: Informatica - name: Rivery - name: RudderStack - name: Snowplow - name: dbt Labs - name: Matillion - name: Prophecy - name: Alteryx - name: Dataiku - name: John Snow Labs - name: Labelbox - name: SuperAnnotate - name: Hex - name: Power BI - name: Preset - name: Qlik - name: Sigma Computing - name: Tableau - name: ThoughtSpot - name: Census - name: Hightouch - name: Hunters - name: Privacera - name: Anomalo - name: erwin - name: Lightup - name: Monte Carlo - name: Precisely - name: AtScale - name: Stardog maintainers: - FN: Kin Lane email: kin@apievangelist.com - name: Databricks email: support@databricks.com url: https://www.databricks.com/ specificationVersion: '0.19' common: - type: AgenticAccess url: agentic-access/databricks-agentic-access.yml - type: VulnerabilityDisclosure url: security/databricks-vulnerability-disclosure.yml - type: DomainSecurity url: security/databricks-domain-security.yml - type: Authentication url: authentication/databricks-authentication.yml - type: MCPServer url: https://docs.databricks.com/aws/en/generative-ai/mcp/ name: MCP Server description: Databricks managed MCP servers for Unity Catalog functions, Genie spaces, Databricks SQL, and Vector Search, with Unity Catalog permissions always enforced. - type: PostmanWorkspace url: https://www.postman.com/kinlaneapi/databricks/overview - type: Arazzo url: arazzo/databricks-audit-cluster-events-workflow.yml name: Databricks Audit Cluster Lifecycle Events - type: Arazzo url: arazzo/databricks-cancel-all-active-runs-workflow.yml name: Databricks Cancel a Job's Active Run - type: Arazzo url: arazzo/databricks-cancel-run-and-confirm-workflow.yml name: Databricks Cancel Job Run and Confirm Terminal - type: Arazzo url: arazzo/databricks-cleanup-workspace-directory-workflow.yml name: Databricks Inspect and Recursively Delete a Directory - type: Arazzo url: arazzo/databricks-clone-job-settings-workflow.yml name: Databricks Clone a Job From an Existing One - type: Arazzo url: arazzo/databricks-create-and-run-job-workflow.yml name: Databricks Create Job and Trigger First Run - type: Arazzo url: arazzo/databricks-delete-job-and-cleanup-runs-workflow.yml name: Databricks Drain Active Runs Then Delete Job - type: Arazzo url: arazzo/databricks-edit-cluster-and-verify-workflow.yml name: Databricks Edit Cluster Configuration and Verify - type: Arazzo url: arazzo/databricks-export-and-reimport-notebook-workflow.yml name: Databricks Export a Notebook and Re-Import as a Copy - type: Arazzo url: arazzo/databricks-find-cluster-and-start-workflow.yml name: Databricks Find Terminated Cluster by Name and Start It - type: Arazzo url: arazzo/databricks-find-job-and-run-workflow.yml name: Databricks Find Job by Name and Run It - type: Arazzo url: arazzo/databricks-import-notebook-and-verify-workflow.yml name: Databricks Create Directory and Import Notebook - type: Arazzo url: arazzo/databricks-latest-run-output-workflow.yml name: Databricks Fetch Latest Completed Run Output for a Job - type: Arazzo url: arazzo/databricks-provision-cluster-and-create-job-workflow.yml name: Databricks Provision Cluster Then Create Job On It - type: Arazzo url: arazzo/databricks-provision-cluster-workflow.yml name: Databricks Provision Cluster and Wait Until Running - type: Arazzo url: arazzo/databricks-restart-cluster-and-verify-workflow.yml name: Databricks Restart Cluster and Verify Running - type: Arazzo url: arazzo/databricks-run-job-and-export-notebook-workflow.yml name: Databricks Run Job, Wait, Then Export the Notebook - type: Arazzo url: arazzo/databricks-run-job-and-wait-workflow.yml name: Databricks Trigger Job Run and Wait for Output - type: Arazzo url: arazzo/databricks-run-job-on-failure-export-output-workflow.yml name: Databricks Run Job and Branch on Success or Failure - type: Arazzo url: arazzo/databricks-stage-notebook-and-create-job-workflow.yml name: Databricks Stage Notebook Then Create and Run a Job - type: Arazzo url: arazzo/databricks-start-cluster-and-run-job-workflow.yml name: Databricks Start Cluster Then Run Job - type: Arazzo url: arazzo/databricks-terminate-and-delete-cluster-workflow.yml name: Databricks Terminate Then Permanently Delete Cluster - type: Arazzo url: arazzo/databricks-update-job-and-rerun-workflow.yml name: Databricks Update Job Settings and Re-Run - url: https://docs.databricks.com/dev-tools/auth.html type: Authentication - url: https://docs.databricks.com/getting-started/index.html type: GettingStarted - url: https://docs.databricks.com/dev-tools/sdks.html type: SDKs - url: https://status.databricks.com/ type: StatusPage - url: https://help.databricks.com/ type: Support - url: https://docs.databricks.com/api/workspace/introduction type: APIReference - url: https://docs.databricks.com/aws/en/reference/api type: Documentation - url: https://www.databricks.com/product/pricing type: Pricing - url: https://www.databricks.com/try-databricks type: Signup - url: https://www.databricks.com/legal/privacynotice type: PrivacyPolicy - url: https://www.databricks.com/legal/terms-of-use type: TermsOfService - url: https://www.databricks.com/trust type: Security - url: https://docs.databricks.com/aws/en/resources/limits type: RateLimits - url: https://docs.databricks.com/aws/en/release-notes/ type: ChangeLog - url: https://www.databricks.com/blog type: Blog - url: https://community.databricks.com/ type: Support title: Community Forum - url: https://github.com/databricks type: GitHubOrganization - url: https://github.com/databricks/databricks-sdk-py type: SDKs title: Python SDK - url: https://github.com/databricks/databricks-sdk-go type: SDKs title: Go SDK - url: https://github.com/databricks/cli type: CLI - url: https://docs.databricks.com/aws/en/dev-tools/cli type: Documentation - url: https://twitter.com/databricks type: X - url: https://www.linkedin.com/company/databricks type: LinkedIn - url: https://login.databricks.com/ type: Login - url: https://www.databricks.com/company/contact type: Contact - url: https://www.databricks.com/learn/training/home type: Training - url: https://customer-academy.databricks.com/learn type: Academy - url: https://github.com/databricks/databricks-sdk-java type: SDKs title: Java SDK - url: https://github.com/databricks/databricks-sql-python type: SDKs title: Python SQL SDK - url: https://github.com/databricks/terraform-provider-databricks type: SDKs title: Terraform Provider - url: https://docs.databricks.com/aws/en/reference/mlflow-api type: APIReference title: MLflow API Reference - url: https://www.databricks.com/trust/security-features type: Security - url: https://docs.databricks.com/aws/en/dev-tools/auth type: Authentication - url: https://api-docs.databricks.com/ type: APIReference - url: openapi/databricks-openapi.yml type: OpenAPI - url: json-schema/databricks-cluster-schema.json type: JSONSchema - url: json-schema/databricks-job-schema.json type: JSONSchema - url: json-ld/databricks-context.jsonld type: JSONLD - url: rules/databricks-spectral-rules.yml type: SpectralRules - type: Features data: - 'Jobs Compute: ~$0.07-$0.15/DBU (cheapest)' - 'All-Purpose Compute: ~$0.55/DBU (interactive)' - 'SQL Serverless: ~$0.70/DBU (infra included)' - 'Serverless Jobs: $0.35-$0.40/DBU' - 'Editions: Standard (Azure legacy), Premium (default), Enterprise (AWS)' - 'Multi-cloud: AWS, Azure, GCP' - 'REST API: 30 req/sec default, 10 req/sec for jobs/run-now' - DBSQL Statement Execution API - Unity Catalog for governance - Delta Lake table format - Mosaic AI / MLflow for ML lifecycle - Genie / AI/BI for natural-language analytics - Workflows for orchestration - Lakeflow Connect for data ingestion - Model Serving for low-latency inference - Committed Use Contracts for volume discounts sources: - https://www.databricks.com/product/pricing updated: '2026-05-04' - type: UseCases data: - name: Data Engineering description: Build and orchestrate ETL pipelines with Delta Live Tables and multi-task workflows. - name: Data Warehousing description: Run analytical SQL queries on lakehouse data with serverless SQL warehouses. - name: Machine Learning description: Train, track, and deploy ML models with MLflow experiment tracking and model registry. - name: Real-Time Analytics description: Process streaming data with structured streaming and serve results through online tables. - name: Data Governance description: Govern data assets across the organization with Unity Catalog metadata management. - type: Integrations data: - name: Apache Spark description: Native integration with Apache Spark for distributed data processing at scale. - name: Delta Lake description: Built on Delta Lake open format for ACID transactions and time travel on data lakes. - name: MLflow description: Open-source platform for managing the complete machine learning lifecycle. - name: Terraform description: Infrastructure-as-code provider for automating Databricks workspace provisioning. - name: dbt description: Integration with dbt for SQL-based data transformation workflows. - type: Integrations url: https://docs.databricks.com/aws/en/integrations - name: Agent Skills url: https://github.com/databricks/databricks-agent-skills type: AgentSkills - type: LlmsText url: https://docs.databricks.com/llms.txt