==============================================================================$$$Databricks ODBC Data Connector Release Notes$$$==============================================================================$$$$$$The release notes provide details of enhancements; features; known issues; and$$$workflow changes in Databricks ODBC Connector 2.12.0; as well as the$$$version history.$$$$$$This version of the driver supports the following data source versions and$$$platforms:$$$$$$ * DBR versions 11.3 LTS to 17.3 LTS$$$$$$ * Windows 11; Windows Server 2025; 2022; 2019; 2016; 2012$$$ * macOS 14; 15; 26$$$ * Debian 11$$$ * RHEL 8; 8ARM; 9; 9ARM; 10; 10ARM; AL2023 ARM$$$ * SLES 15; 16$$$ * Ubuntu 22.04; 24.04$$$$$$$$$2.12.0 =======================================================================$$$$$$Released 2026-6-12$$$$$$Enhancements & New Features$$$$$$ * [SPARKO-1756] SQLProcedures and SQLProcedureColumns support.$$$$$$ The connector now supports SQLProcedures and SQLProcedureColumns catalog$$$ functions for retrieving stored procedure metadata when connected to$$$ Databricks 17.0 and later.$$$$$$ * [SPARKO-1691] Case-insensitive metadata filters.$$$$$$ The connector now supports case-insensitive metadata filters for catalog$$$ functions.$$$$$$ To enable this feature; set CaseInsensitiveMetadataFilter to 1. For more$$$ information; see the Installation and Configuration Guide.$$$$$$ * [SPARKO-1661] Use the Arrow data type for decimals.$$$$$$ The connector now enables decimalAsArrow for decimal data types. This can$$$ be turned off by setting the connection flag DecimalAsArrow=0.$$$$$$ * [SPARKO-1721] Arrow data performance improvements.$$$$$$ This release improves performance when using Arrow data.$$$$$$ * [SPARKO-1728] Bulk fetch performance improvements.$$$$$$ This release improves bulk fetch performance.$$$$$$ * [SPARKO-1674] TLS handshake failure logging improvements.$$$$$$ Server certificates are reported in the log file when there is an error$$$ during SSL handshakes.$$$$$$ * [SPARKO-1658] Previously updated: UseNativeQuery default value$$$$$$ As part of SQL stored procedure support added in connector version 2.11.0;$$$ the default value of UseNativeQuery has been updated to 1 (enabled).$$$$$$ * [SPARKO-1775] SLES 16 support$$$$$$ The connector now supports SLES 16.$$$$$$ * [SPARKO-1798] [SPARKO-1810] Updated third-party libraries$$$$$$ The connector now uses the following third-party libraries:$$$ - Expat 2.8.1 (previously 2.7.4)$$$ - libcURL 8.20.0 (previously 8.18.0)$$$ - OpenSSL 3.5.7 (previously 3.0.19)$$$ - Thrift 0.23.0 (previously 0.17.0)$$$ - zlib 1.3.2 (previously 1.3.1)$$$

==============================================================================$$$Databricks ODBC Data Connector Release Notes$$$==============================================================================$$$$$$The release notes provide details of enhancements; features; known issues; and$$$workflow changes in Databricks ODBC Connector 2.12.0; as well as the$$$version history.$$$$$$This version of the driver supports the following data source versions and$$$platforms:$$$$$$ * DBR versions 11.3 LTS to 17.3 LTS$$$$$$ * Windows 11; Windows Server 2025; 2022; 2019; 2016; 2012$$$ * macOS 14; 15; 26$$$ * Debian 11$$$ * RHEL 8; 8ARM; 9; 9ARM; 10; 10ARM; AL2023 ARM$$$ * SLES 15; 16$$$ * Ubuntu 22.04; 24.04$$$$$$$$$2.12.0 =======================================================================$$$$$$Released 2026-6-12$$$$$$Enhancements & New Features$$$$$$ * [SPARKO-1756] SQLProcedures and SQLProcedureColumns support.$$$$$$ The connector now supports SQLProcedures and SQLProcedureColumns catalog$$$ functions for retrieving stored procedure metadata when connected to$$$ Databricks 17.0 and later.$$$$$$ * [SPARKO-1691] Case-insensitive metadata filters.$$$$$$ The connector now supports case-insensitive metadata filters for catalog$$$ functions.$$$$$$ To enable this feature; set CaseInsensitiveMetadataFilter to 1. For more$$$ information; see the Installation and Configuration Guide.$$$$$$ * [SPARKO-1661] Use the Arrow data type for decimals.$$$$$$ The connector now enables decimalAsArrow for decimal data types. This can$$$ be turned off by setting the connection flag DecimalAsArrow=0.$$$$$$ * [SPARKO-1721] Arrow data performance improvements.$$$$$$ This release improves performance when using Arrow data.$$$$$$ * [SPARKO-1728] Bulk fetch performance improvements.$$$$$$ This release improves bulk fetch performance.$$$$$$ * [SPARKO-1674] TLS handshake failure logging improvements.$$$$$$ Server certificates are reported in the log file when there is an error$$$ during SSL handshakes.$$$$$$ * [SPARKO-1658] Previously updated: UseNativeQuery default value$$$$$$ As part of SQL stored procedure support added in connector version 2.11.0;$$$ the default value of UseNativeQuery has been updated to 1 (enabled).$$$$$$ * [SPARKO-1775] SLES 16 support$$$$$$ The connector now supports SLES 16.$$$$$$ * [SPARKO-1798] [SPARKO-1810] Updated third-party libraries$$$$$$ The connector now uses the following third-party libraries:$$$ - Expat 2.8.1 (previously 2.7.4)$$$ - libcURL 8.20.0 (previously 8.18.0)$$$ - OpenSSL 3.5.7 (previously 3.0.19)$$$ - Thrift 0.23.0 (previously 0.17.0)$$$ - zlib 1.3.2 (previously 1.3.1)$$$

2.12.1 =======================================================================$$$$$$Released 2026-7-17$$$$$$ * [SPARKO-1847] Updated third-party libraries$$$$$$ The connector now uses the following third-party libraries:$$$ - Expat 2.8.2 (previously 2.8.1)$$$ - libcURL 8.21.0 (previously 8.20.0)$$$$$$$$$Known Issues$$$The following are known issues that you may encounter due to limitations in$$$the data source; the connector; or an application.$$$$$$ * [SPARKO-1404] When querying tables that contain VOID columns; the server$$$ returns an error.$$$$$$ * [SPARKO-1101] When the Auth_AccessToken line length is longer than the$$$ maximum limit of 1000; the connector returns an authentication error. For$$$ more information; see the Installation and Configuration Guide.$$$$$$ * [SPARKO-879] When connecting to a server that supports multiple catalogs;$$$ the connector no longer reports the catalog for schemas and tables as$$$ SPARK.$$$$$$ The Spark server now reports the catalog.$$$$$$ * [SPARKO-670] In some cases; when retrieving timestamp data; the connector$$$ returns an error.$$$$$$ In some cases; when connecting to certain distributions of$$$ Apache Spark; the connector returns the following error: Conversion from$$$ number to string failed due to undersized character buffer. This issue$$$ affects versions 2.6.12 to 2.6.14 of the Spark ODBC connector.$$$$$$ As a workaround; set EnableArrow=0 in the connection string or DSN.$$$$$$ * [SPARKO-620] Issue with date and timestamp before the beginning of the$$$ Gregorian calendar when connecting to Spark 2.4.4 or later; or versions$$$ previous to 3.0; with Arrow result set serialization.$$$$$$ When using Spark 2.4.4 or later; or versions previous to Spark 3.0; DATE$$$ and TIMESTAMP data before October 15; 1582 may be returned incorrectly if$$$ the server supports serializing query results using Apache Arrow. This$$$ issue should not impact most distributions of Apache Spark.$$$$$$ To confirm if your distribution of Spark 2.4.4 or later has been impacted$$$ by this issue; you can execute the following query:$$$$$$ SELECT DATE 1581-10-14$$$$$$ If the result returned by the connector is 1581-10-24; then you are$$$ impacted by the issue. In this case; if your data set contains date and/or$$$ timestamp data earlier than October 15; 1582; you can work around this$$$ issue by adding EnableArrow=0 in your DSN or connection string to disable$$$ the Arrow result set serialization feature.$$$$$$ * When retrieving data from a BINARY column; a ClassCastException error$$$ occurs.$$$$$$ In Spark 1.6.3 or earlier; the server sometimes returns a$$$ ClassCastException error when attempting to retrieve data from a BINARY$$$ column.$$$$$$ This issue is fixed as of Spark 2.0.0.$$$$$$ For more information; see the JIRA issue posted by Apache named When$$$ column type is binary; select occurs ClassCastException in Beeline at$$$ https://issues.apache.org/jira/browse/SPARK-12143.$$$$$$$$$Workflow Changes =============================================================$$$$$$The following changes may disrupt established workflows for the connector.$$$$$$$$$2.12.0 -----------------------------------------------------------------------$$$$$$ * [SPARKO-1760] SQL transactions limited to native query mode only.$$$$$$ If the user attempts to use SQL transactions when UseNativeQuery=0; the$$$ connector will throw an error.

==============================================================================$$$Databricks ODBC Data Connector Release Notes$$$==============================================================================$$$$$$The release notes provide details of enhancements; features; known issues; and$$$workflow changes in Databricks ODBC Connector 2.11.0; as well as the$$$version history.$$$$$$This version of the driver supports the following data source versions and$$$platforms:$$$$$$ * DBR versions 11.3 LTS to 17.3 LTS$$$$$$ * Windows 11; Windows Server 2025; 2022; 2019; 2016; 2012$$$ * macOS 14; 15; 26$$$ * Debian 11$$$ * RHEL 8; 8ARM; 9; 9ARM; 10; 10ARM; AL2023 ARM$$$ * SLES 15$$$ * Ubuntu 22.04; 24.04$$$$$$$$$2.11.0 =======================================================================$$$$$$Release 2026-3-20$$$$$$Enhancements & New Features$$$$$$ * [SPARKO-1658] Stored Procedures$$$$$$ The connector now supports SQL stored procedures when using Databricks$$$ Unity Catalog.$$$$$$ * [SPARKO-1572] Telemetry support$$$$$$ The EnableTelemetry connection setting is on by default. When enabled;$$$ telemetry data will be sent to servers that support this feature.$$$$$$ * [SPARKO-1696] Bulk fetch performance improvement$$$$$$ The connector has improved bulk fetch performance.$$$$$$ * [SPARKO-1677] Geospatial datatype metadata improvement$$$$$$ The connector now returns GEOMETRY or GEOGRAPHY for SQL_DESC_TYPE_NAME$$$ on geospatial data types.$$$$$$ * [SPARKO-1735] macOS 26 support$$$$$$ The connector now support macOS 26.$$$$$$ * [SPARKO-1571] [SPARKO-1737] Updated third-party libraries$$$$$$ The connector now uses the following third-party libraries:$$$ - Expat 2.7.4 (previously 2.7.1)$$$ - OpenSSL 3.0.19 (previously 3.0.18)$$$ - libcURL 8.18.0 (previously 8.16.0)$$$$$$$$$Resolved Issues$$$The following issues have been resolved in Databricks ODBC Connector$$$2.11.0.$$$$$$ * [SPARKO-1646] The DriverConfiguration dialog correctly shows the$$$ connector as Databricks ODBC.$$$$$$$$$Known Issues$$$The following are known issues that you may encounter due to limitations in$$$the data source; the connector; or an application.$$$$$$ * [SPARKO-1404] When querying tables that contain VOID columns; the server$$$ returns an error.$$$$$$ * [SPARKO-1101] When the Auth_AccessToken line length is longer than the$$$ maximum limit of 1000; the connector returns an authentication error. For$$$ more information; see the Installation and Configuration Guide.$$$$$$ * [SPARKO-879] When connecting to a server that supports multiple catalogs;$$$ the connector no longer reports the catalog for schemas and tables as$$$ SPARK.$$$$$$ The Spark server now reports the catalog.$$$$$$ * [SPARKO-670] In some cases; when retrieving timestamp data; the connector$$$ returns an error.$$$$$$ In some cases; when connecting to certain distributions of$$$ Apache Spark; the connector returns the following error: Conversion from$$$ number to string failed due to undersized character buffer. This issue$$$ affects versions 2.6.12 to 2.6.14 of the Spark ODBC connector.$$$$$$ As a workaround; set EnableArrow=0 in the connection string or DSN.$$$$$$ * [SPARKO-620] Issue with date and timestamp before the beginning of the$$$ Gregorian calendar when connecting to Spark 2.4.4 or later; or versions$$$ previous to 3.0; with Arrow result set serialization.$$$$$$ When using Spark 2.4.4 or later; or versions previous to Spark 3.0; DATE$$$ and TIMESTAMP data before October 15; 1582 may be returned incorrectly if$$$ the server supports serializing query results using Apache Arrow. This$$$ issue should not impact most distributions of Apache Spark.$$$$$$ To confirm if your distribution of Spark 2.4.4 or later has been impacted$$$ by this issue; you can execute the following query:$$$$$$ SELECT DATE 1581-10-14$$$$$$ If the result returned by the connector is 1581-10-24; then you are$$$ impacted by the issue. In this case; if your data set contains date and/or$$$ timestamp data earlier than October 15; 1582; you can

==============================================================================$$$Databricks ODBC Data Connector Release Notes$$$==============================================================================$$$$$$The release notes provide details of enhancements; features; known issues; and$$$workflow changes in Databricks ODBC Connector 2.11.0; as well as the$$$version history.$$$$$$This version of the driver supports the following data source versions and$$$platforms:$$$$$$ * DBR versions 11.3 LTS to 17.3 LTS$$$$$$ * Windows 11; Windows Server 2025; 2022; 2019; 2016; 2012$$$ * macOS 14; 15; 26$$$ * Debian 11$$$ * RHEL 8; 8ARM; 9; 9ARM; 10; 10ARM; AL2023 ARM$$$ * SLES 15$$$ * Ubuntu 22.04; 24.04$$$$$$$$$2.11.0 =======================================================================$$$$$$Release 2026-3-20$$$$$$Enhancements & New Features$$$$$$ * [SPARKO-1658] Stored Procedures$$$$$$ The connector now supports SQL stored procedures when using Databricks$$$ Unity Catalog.$$$$$$ * [SPARKO-1572] Telemetry support$$$$$$ The EnableTelemetry connection setting is on by default. When enabled;$$$ telemetry data will be sent to servers that support this feature.$$$$$$ * [SPARKO-1696] Bulk fetch performance improvement$$$$$$ The connector has improved bulk fetch performance.$$$$$$ * [SPARKO-1677] Geospatial datatype metadata improvement$$$$$$ The connector now returns GEOMETRY or GEOGRAPHY for SQL_DESC_TYPE_NAME$$$ on geospatial data types.$$$$$$ * [SPARKO-1735] macOS 26 support$$$$$$ The connector now support macOS 26.$$$$$$ * [SPARKO-1571] [SPARKO-1737] Updated third-party libraries$$$$$$ The connector now uses the following third-party libraries:$$$ - Expat 2.7.4 (previously 2.7.1)$$$ - OpenSSL 3.0.19 (previously 3.0.18)$$$ - libcURL 8.18.0 (previously 8.16.0)$$$$$$$$$Resolved Issues$$$The following issues have been resolved in Databricks ODBC Connector$$$2.11.0.$$$$$$ * [SPARKO-1646] The DriverConfiguration dialog correctly shows the$$$ connector as Databricks ODBC.$$$$$$$$$Known Issues$$$The following are known issues that you may encounter due to limitations in$$$the data source; the connector; or an application.$$$$$$ * [SPARKO-1404] When querying tables that contain VOID columns; the server$$$ returns an error.$$$$$$ * [SPARKO-1101] When the Auth_AccessToken line length is longer than the$$$ maximum limit of 1000; the connector returns an authentication error. For$$$ more information; see the Installation and Configuration Guide.$$$$$$ * [SPARKO-879] When connecting to a server that supports multiple catalogs;$$$ the connector no longer reports the catalog for schemas and tables as$$$ SPARK.$$$$$$ The Spark server now reports the catalog.$$$$$$ * [SPARKO-670] In some cases; when retrieving timestamp data; the connector$$$ returns an error.$$$$$$ In some cases; when connecting to certain distributions of$$$ Apache Spark; the connector returns the following error: Conversion from$$$ number to string failed due to undersized character buffer. This issue$$$ affects versions 2.6.12 to 2.6.14 of the Spark ODBC connector.$$$$$$ As a workaround; set EnableArrow=0 in the connection string or DSN.$$$$$$ * [SPARKO-620] Issue with date and timestamp before the beginning of the$$$ Gregorian calendar when connecting to Spark 2.4.4 or later; or versions$$$ previous to 3.0; with Arrow result set serialization.$$$$$$ When using Spark 2.4.4 or later; or versions previous to Spark 3.0; DATE$$$ and TIMESTAMP data before October 15; 1582 may be returned incorrectly if$$$ the server supports serializing query results using Apache Arrow. This$$$ issue should not impact most distributions of Apache Spark.$$$$$$ To confirm if your distribution of Spark 2.4.4 or later has been impacted$$$ by this issue; you can execute the following query:$$$$$$ SELECT DATE 1581-10-14$$$$$$ If the result returned by the connector is 1581-10-24; then you are$$$ impacted by the issue. In this case; if your data set contains date and/or$$$ timestamp data earlier than October 15; 1582; you can