Databricks is a data analytics platform that provides data lakehouse solutions for businesses, combining data warehouses and data lakes to offer unified analytics for data engineering, machine learning, and business intelligence.
Why this server?
Provides SQL interface for Databricks data warehousing and analytics platform.
Why this server?
Enables querying of Databricks data through relational SQL models.
Why this server?
Enables read-only access to Databricks data via SQL models.
Why this server?
Allows querying Databricks data through a SQL interface, providing access to tables and data in Databricks environments.
Why this server?
Allows querying Databricks tables and data through SQL, exposing Databricks data as relational tables.
Why this server?
Listed as a supported data source that can be accessed through the CData JDBC driver integration.
Why this server?
Allows retrieval of SAS Data Sets containing Databricks data via SQL queries.
Why this server?
Listed as a supported data source for integration through the CData JDBC driver.
Why this server?
Listed as a supported data source in the compatibility table, enabling access to Databricks data.
Why this server?
Allows querying Databricks data analytics platform in a read-only format.
Why this server?
Allows querying Databricks data lake and analytics platform via SQL.
Why this server?
Provides SQL access to Databricks tables and data sources.
Why this server?
Listed as a supported data source that can be connected to through the CData JDBC driver.
Why this server?
Allows querying data stored in Databricks tables and datasets.
Why this server?
Provides access to Databricks analytics platform data through SQL queries.
Why this server?
Allows querying Databricks data lake and analytics platform through SQL.
Why this server?
Allows querying Databricks data by exposing it as relational tables, with tools for listing tables, retrieving column information, and executing SQL queries.
Why this server?
Provides SQL-based access to data stored in Databricks.
Why this server?
Listed as a supported data source that can be integrated with the MCP server for data access.
Why this server?
Allows querying Databricks data lakes and databases through a SQL interface
Why this server?
Allows retrieval of data from Databricks analytics platform through SQL-based tools for listing tables, retrieving column information, and executing SELECT queries.
Why this server?
Listed as a supported data source for accessing Databricks data and analytics.
Why this server?
Enables SQL-based querying of Databricks data and analytics.
Why this server?
Listed as a supported data source that can be connected to through the CData JDBC driver, enabling data querying capabilities.
Why this server?
Provides read-only access to data stored in Databricks, allowing queries against live Databricks data using natural language instead of SQL. The MCP server exposes Databricks data as relational SQL models for retrieval.
Why this server?
Provides access to Databricks data by exposing it as relational SQL models through the CData JDBC Driver.
Why this server?
Listed as a supported data source that can be accessed through the CData JDBC driver, allowing for data retrieval from Databricks analytics platform.
Why this server?
Provides SQL-based access to Databricks data lakes and warehouses through natural language queries.
Why this server?
Enables querying Databricks data through a SQL interface via the MCP server.
Why this server?
Provides SQL-based access to Databricks data and workspaces.
Why this server?
Allows querying Databricks data through SQL interfaces, making data lakehouse information accessible via natural language.
Why this server?
Enables SQL queries against Databricks data warehouses, notebooks, and analytics environments.
Why this server?
Listed as a supported data source for integration through the CData JDBC Driver
Why this server?
Provides access to Databricks workspace, notebooks, and data through SQL queries.
Why this server?
Provides SQL interface for accessing Databricks data.
Why this server?
Listed as a supported data source for integration with the MCP server, allowing access to Databricks data.
Why this server?
Enables SQL-based access to Databricks workspaces, allowing queries against data lakes and other Databricks-managed data sources.
Why this server?
Enables querying Databricks data through a SQL interface.
Why this server?
Provides access to Databricks data analytics platform through SQL queries.
Why this server?
Listed as a supported data source that can be accessed through CData JDBC Driver and exposed via the MCP server.
Why this server?
Provides access to data stored in Databricks workspaces through SQL interfaces.
Why this server?
Allows querying Databricks data through natural language questions rather than writing SQL.
Why this server?
Included in the list of supported sources for data retrieval through the MCP server.
Why this server?
Provides read-only access to Databricks data, allowing retrieval of information through natural language questions without requiring SQL knowledge.
Why this server?
Enables access to Databricks data and analytics information through SQL queries.
Why this server?
Enables SQL queries against Databricks data and notebooks.
Why this server?
Enables access to Databricks data and analytics through SQL queries.
Why this server?
Executes SQL queries against Databricks using the Statement Execution API, allowing data retrieval, schema listing, table enumeration, and table schema description through the Databricks platform.
Why this server?
Provides tools for interacting with Databricks workspaces, allowing users to list catalogs, schemas, and tables, execute SQL statements, and retrieve information about SQL warehouses.
Why this server?
Enables read-only access to Databricks data, allowing SQL queries against data lakes and other Databricks resources.
Why this server?
Connects to Databricks API, allowing SQL query execution on Databricks warehouses, listing of jobs, retrieving job status, and accessing detailed job information.
Why this server?
Provides access to Databricks functionality through tools that allow interacting with clusters (listing, creating, terminating, starting), jobs (listing, running), notebooks (listing, exporting), files (browsing DBFS paths), and executing SQL queries on a Databricks instance.