ODBC (Open Database Connectivity) and JDBC (Java Database Connectivity) are standardized APIs that allow applications to communicate with databases through a uniform interface. ODBC originated in 1992 and is used primarily by Windows applications and BI tools (Tableau, Excel, Power BI, MicroStrategy). JDBC, introduced with Java in 1997, is used by Java-based applications and enterprise software.
Why ODBC/JDBC Still Matter
Despite the emergence of superior protocols like Arrow Flight SQL, ODBC and JDBC remain essential in enterprise lakehouse deployments because virtually every BI tool, spreadsheet application, and legacy reporting system supports them. Connecting Tableau to a Dremio lakehouse, or enabling Excel ODBC to query an Iceberg table through Dremio, is a standard enterprise use case that ODBC/JDBC addresses reliably.
ODBC/JDBC in the Lakehouse Stack
Modern query engines like Dremio, Trino, and Databricks expose ODBC and JDBC endpoints. These drivers translate the engine's native wire protocol into the standardized ODBC/JDBC interface expected by client tools. The JDBC driver for Dremio, for example, allows any Java application to submit SQL queries to Dremio's distributed lakehouse engine and receive results as standard Java ResultSets.
Performance Considerations
ODBC and JDBC serialize data into row-oriented formats during transit, introducing overhead for large analytical result sets compared to Arrow Flight SQL. For BI dashboards where a query returns thousands to millions of rows to a Tableau visualization, this serialization overhead is measurable. High-performance lakehouse architectures often configure BI tools to use Arrow Flight SQL drivers where available (Tableau, Power BI, and Dremio all support Flight SQL connectivity), reserving ODBC/JDBC for legacy applications that cannot be migrated.
