October 2025 monthly summary for duckdb/duckdb-odbc focusing on CI reliability and Windows ARM64 artifact signing. Implemented Azure Code Signing environment variables to enable proper signing of ARM64 artifacts in CI, addressing missing env vars and reducing signing failures. This aligns with improving artifact integrity and CI reliability for Windows ARM64 distributions.

September 2025 (2025-09) — ODBC driver for DuckDB: delivered cross‑platform stability and CI enhancements, corrected API surface and symbols, expanded Windows ARM64 CI, and strengthened test coverage. Key outcomes include stabilized Linux builds by re-enabling GCC 12, improved macOS symbol exports and harmonized API signatures across platforms, expanded Windows ARM64 CI/build support, and corrected SQLNumResultCols reporting with added tests. These changes enhance reliability for production deployments, broaden platform support, and strengthen test coverage, delivering tangible business value for customers relying on cross‑platform ODBC connectivity while reducing integration risk.

Monthly summary for 2025-08 focused on stabilizing the duckdb-odbc Linux CI and ensuring API compatibility with the core DuckDB project. Key actions included reverting the GCC 12 downgrade for Linux builds to restore CI stability and removing gcc-toolset-12 from the ODBC CI workflow, addressing build issues highlighted in duckdb/duckdb#17963. In parallel, the ODBC API surface was aligned with main DuckDB C-API changes by updating the exported symbols (duckdb_odbc.def, duckdb_odbc.exp, duckdb_odbc.map).

June 2025 monthly summary: Delivered key cross-platform enhancements to the duckdb-odbc driver with a focus on stability, compatibility, and engineer productivity. Implemented a bug fix for non-null-terminated connection strings, introduced runtime compatibility with older C++ standard libraries, and stabilized CI/CD across Windows, Linux, and macOS with improved packaging and vendoring tests. These changes reduce integration risk for enterprise deployments and improve resilience when loading host processes with diverse toolchains.

Summary for 2025-05: Delivered key ODBC driver enhancements (duckdb-odbc) that improve reliability, performance, and interoperability, with strong test coverage and CI improvements. Highlights include unbound parameter execution, TIMESTAMP WITH TIME ZONE handling, large data retrieval in parts, startup optimization, and CI artifact hygiene; plus targeted bug fixes and quality improvements that tighten type mappings and SQLTables semantics.

Monthly summary for 2025-04 (duckdb/duckdb-odbc). Focused on delivering measurable business value through robust CI/CD improvements, feature enhancements, and stability fixes that advance cross-platform reliability and internationalization for the ODBC driver. Key outcomes include improved release velocity, broader Unicode support, automated extension management, and enhanced metadata querying capabilities, all backed by targeted tests and cross-platform build optimizations.

Month 2025-03: Delivered a focused set of ODBC driver enhancements for DuckDB that improve data compatibility, cross-platform reliability, and developer/test tooling. Key work spanned new encoding utilities, extended data type support, and CI/Windows integration improvements. The combined impact is better PowerBI/PyODBC compatibility, simpler MS Access workflows, and faster iteration through automated Windows testing.

February 2025 monthly summary for duckdb-odbc: Focused on stability, compatibility, and diagnostic reliability to enable broader tool interoperability and reduce support risk. Delivered core feature enhancements for external tool connectivity, Unicode parameter support, and maintained test quality aligned with upstream changes.

January 2025 monthly summary: Focused on improving data correctness, reliability, and installer resilience across core data integration components. Delivered a safety enhancement for Continuous Aggregates refresh in timescale/timescaledb, and fixed critical DSN parsing and installer behavior in duckdb-odbc, with added tests to validate changes. These efforts reduce operational risk, improve data consistency, and enhance user experience for enterprise deployments.