{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-databricks-sqltools-databricks-driver","slug":"databricks-driver-for-sqltools","name":"Databricks Driver for SQLTools","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=databricks.sqltools-databricks-driver","page_url":"https://unfragile.ai/databricks-driver-for-sqltools","categories":["code-editors"],"tags":["data science","data warehouse","databricks","databricks sql","dbsql","lakehouse","machine learning","ml","sql","sqltools-driver"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-databricks-sqltools-databricks-driver__cap_0","uri":"capability://tool.use.integration.databricks.workspace.connection.management.via.sqltools.integration","name":"databricks workspace connection management via sqltools integration","description":"Establishes authenticated connections to Databricks SQL warehouses and all-purpose clusters through SQLTools' connection registry system. The driver acts as an adapter layer that translates SQLTools' generic database connection interface into Databricks-specific authentication and endpoint handling, supporting both interactive workspace selection and programmatic connection configuration. Connections are persisted in VS Code's secure credential storage and made available to all SQLTools operations within the editor.","intents":["Connect to a Databricks workspace from VS Code without leaving the editor","Switch between multiple Databricks workspaces or compute resources","Store and reuse Databricks credentials securely across VS Code sessions","Configure different connection profiles for development, staging, and production Databricks instances"],"best_for":["Data engineers working with Databricks SQL warehouses in VS Code","Analytics teams managing multiple Databricks workspaces","Organizations standardizing on SQLTools for multi-database query management"],"limitations":["Requires SQLTools extension as a hard dependency — cannot function standalone","Connection configuration method varies by compute type (SQL warehouse vs all-purpose cluster) with unclear UI/UX differences","No documented support for Databricks personal access token rotation or credential refresh workflows","Credential storage mechanism not documented — unclear if using VS Code's native secret storage or alternative approach"],"requires":["Visual Studio Code (version not specified in documentation)","SQLTools extension (version not specified)","Valid Databricks workspace URL and authentication credentials","Network connectivity to Databricks control plane and compute endpoints"],"input_types":["connection configuration object (workspace URL, compute resource identifier, authentication token)","user input via connection creation form"],"output_types":["authenticated connection object registered in SQLTools connection registry","connection metadata (workspace name, compute type, catalog/schema context)"],"categories":["tool-use-integration","database-connectivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-databricks-sqltools-databricks-driver__cap_1","uri":"capability://search.retrieval.databricks.object.browser.with.catalog.schema.table.hierarchy.navigation","name":"databricks object browser with catalog-schema-table hierarchy navigation","description":"Provides a hierarchical tree view in the SQLTools sidebar that enumerates Databricks objects (catalogs, schemas, tables, views) for the currently selected connection. The driver queries Databricks metadata APIs to populate the object tree dynamically, enabling point-and-click navigation and object inspection without manual schema queries. Clicking objects inserts their fully-qualified names into the editor, supporting the three-level Databricks namespace (catalog.schema.table).","intents":["Browse available tables and views in a Databricks workspace without writing metadata queries","Quickly insert table names into SQL queries by clicking in the object browser","Discover schema structure and available objects in unfamiliar Databricks workspaces","Navigate between catalogs and schemas when working with Unity Catalog"],"best_for":["Data analysts exploring Databricks schemas interactively","SQL developers new to a Databricks workspace who need schema discovery","Teams using Unity Catalog with multiple catalogs requiring cross-catalog navigation"],"limitations":["Object browser refresh behavior not documented — unclear if automatic or manual refresh required","No filtering or search capability mentioned for large schemas with hundreds of tables","Performance impact on large workspaces with many catalogs/schemas unknown","No support for viewing object metadata (column types, descriptions, partitioning) directly in tree view"],"requires":["Active Databricks connection configured in SQLTools","Permissions to access INFORMATION_SCHEMA or Databricks metadata APIs","SQLTools extension with sidebar UI support"],"input_types":["connection context (selected workspace and compute resource)","user click/selection events on tree nodes"],"output_types":["hierarchical object tree (catalogs → schemas → tables/views)","fully-qualified object names (catalog.schema.table) inserted into editor"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-databricks-sqltools-databricks-driver__cap_2","uri":"capability://data.processing.analysis.sql.query.execution.against.databricks.with.result.streaming","name":"sql query execution against databricks with result streaming","description":"Executes SQL queries typed in VS Code editor against the selected Databricks connection and streams results back to the SQLTools results panel. The driver translates SQLTools' query execution interface into Databricks SQL API calls, handling query submission, polling for completion, and result fetching. Results are displayed in a tabular format within VS Code with support for pagination and export (export format not documented).","intents":["Run ad-hoc SQL queries against Databricks directly from the editor","Execute multi-statement SQL scripts with result inspection","Test SQL logic before deploying to production Databricks jobs","Inspect query results and export data for analysis"],"best_for":["Data engineers and analysts writing and testing SQL against Databricks","Teams using VS Code as their primary SQL IDE for Databricks","Developers iterating on SQL logic before productionizing in notebooks or jobs"],"limitations":["Query timeout behavior not documented — unclear if there are limits on long-running queries","Result set size limits not specified — potential memory issues with very large result sets","No documented support for query cancellation mid-execution","Export format options not documented — unclear what formats are supported","No query optimization or EXPLAIN PLAN visualization mentioned","Transaction management not documented — unclear if multi-statement scripts are atomic"],"requires":["Active Databricks connection with query execution permissions","SQL query text in VS Code editor","Sufficient compute resources in selected Databricks warehouse/cluster"],"input_types":["SQL query text (single or multi-statement)","connection context (selected warehouse/cluster)"],"output_types":["tabular result set displayed in SQLTools results panel","query execution metadata (rows affected, execution time)","exported data (format unknown)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-databricks-sqltools-databricks-driver__cap_3","uri":"capability://tool.use.integration.compute.type.aware.connection.configuration.routing","name":"compute type-aware connection configuration routing","description":"Provides different connection configuration workflows depending on whether the user is connecting to a Databricks SQL warehouse or an all-purpose cluster. The driver detects or prompts for compute type selection and routes to appropriate configuration forms with compute-specific fields and validation. Implementation details of the type-specific configuration differences are not documented in available materials.","intents":["Configure connections to SQL warehouses with warehouse-specific settings","Configure connections to all-purpose clusters with cluster-specific settings","Avoid configuration errors by using compute-type-appropriate forms","Switch between warehouse and cluster connections for the same workspace"],"best_for":["Organizations using both SQL warehouses and all-purpose clusters in Databricks","Teams with different compute preferences across projects","Users managing multiple compute resources in a single workspace"],"limitations":["Specific configuration fields for each compute type not documented","Unclear how to switch compute type for existing connections","No documentation of compute type detection logic or manual override options","Performance characteristics of each compute type not addressed in driver documentation"],"requires":["Knowledge of whether connecting to SQL warehouse or all-purpose cluster","Appropriate credentials and permissions for selected compute type"],"input_types":["compute type selection (SQL warehouse or all-purpose cluster)","compute-type-specific configuration parameters"],"output_types":["validated connection configuration object","connection metadata indicating compute type"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-databricks-sqltools-databricks-driver__cap_4","uri":"capability://tool.use.integration.sqltools.ecosystem.integration.and.command.palette.access","name":"sqltools ecosystem integration and command palette access","description":"Registers as a driver within the SQLTools extension ecosystem, making Databricks connections available to all SQLTools commands and workflows. The driver exposes Databricks-specific commands through VS Code's command palette and integrates with SQLTools' connection management UI, allowing users to manage Databricks connections alongside other database connections. Integration follows SQLTools' driver plugin architecture with standardized interfaces for connection, query execution, and object browsing.","intents":["Use Databricks connections with all existing SQLTools commands and extensions","Manage Databricks connections in the same UI as other database connections","Access Databricks-specific commands through VS Code command palette","Combine Databricks queries with other database operations in SQLTools workflows"],"best_for":["Teams using SQLTools for multi-database management who want to add Databricks","Organizations with heterogeneous data stacks (Databricks + PostgreSQL + Snowflake, etc.)","Developers familiar with SQLTools who want consistent UX across all databases"],"limitations":["Dependent on SQLTools extension — cannot function if SQLTools is uninstalled or disabled","SQLTools version compatibility not documented — unclear if driver works with all SQLTools versions","Custom SQLTools extensions or plugins may have compatibility issues with Databricks driver","No documented support for SQLTools features that may not apply to Databricks (e.g., certain export formats)"],"requires":["SQLTools extension installed and enabled","VS Code command palette access (Ctrl+Shift+P / Cmd+Shift+P)","SQLTools sidebar visible for connection management"],"input_types":["SQLTools command invocations","connection selection from SQLTools UI"],"output_types":["Databricks connection available to all SQLTools operations","command palette results for Databricks-specific commands","integrated connection management UI"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Visual Studio Code (version not specified in documentation)","SQLTools extension (version not specified)","Valid Databricks workspace URL and authentication credentials","Network connectivity to Databricks control plane and compute endpoints","Active Databricks connection configured in SQLTools","Permissions to access INFORMATION_SCHEMA or Databricks metadata APIs","SQLTools extension with sidebar UI support","Active Databricks connection with query execution permissions","SQL query text in VS Code editor","Sufficient compute resources in selected Databricks warehouse/cluster"],"failure_modes":["Requires SQLTools extension as a hard dependency — cannot function standalone","Connection configuration method varies by compute type (SQL warehouse vs all-purpose cluster) with unclear UI/UX differences","No documented support for Databricks personal access token rotation or credential refresh workflows","Credential storage mechanism not documented — unclear if using VS Code's native secret storage or alternative approach","Object browser refresh behavior not documented — unclear if automatic or manual refresh required","No filtering or search capability mentioned for large schemas with hundreds of tables","Performance impact on large workspaces with many catalogs/schemas unknown","No support for viewing object metadata (column types, descriptions, partitioning) directly in tree view","Query timeout behavior not documented — unclear if there are limits on long-running queries","Result set size limits not specified — potential memory issues with very large result sets","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.58,"quality":0.2,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.118Z","last_scraped_at":"2026-05-03T15:20:36.253Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=databricks-driver-for-sqltools","compare_url":"https://unfragile.ai/compare?artifact=databricks-driver-for-sqltools"}},"signature":"Opxu5hoheUO4YL4j6TgavWtqoqljQKYl+rIOiyJPgqywxBmpqvU/7sGm0l4ljC6RgNaDQ8sKdaHtSjkNeUpWBw==","signedAt":"2026-06-22T10:04:42.895Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/databricks-driver-for-sqltools","artifact":"https://unfragile.ai/databricks-driver-for-sqltools","verify":"https://unfragile.ai/api/v1/verify?slug=databricks-driver-for-sqltools","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}