What a year of building ADBC drivers taught Columnar about zero-copy's non-zero problems
Blog post from dbt
Columnar’s experience building production Arrow Database Connectivity (ADBC) drivers shows that ADBC can reduce data-transfer overhead by standardizing database access around Apache Arrow’s columnar in-memory format, but its zero-copy benefits depend heavily on each database’s native protocols and type behavior. Adopted by tools including dbt v2, Power BI, Airflow, dltHub, DuckDB, and Polars, ADBC avoids serialization when systems already return Arrow data, although drivers for platforms using JSON or row-oriented formats must perform conversions. The largest implementation challenges involve inconsistent database semantics for numeric precision, strings, binary data, timestamps, arrays, nulls, and time zones, with examples ranging from Oracle’s empty-string handling to Snowflake’s per-row time-zone offsets and BigQuery’s ambiguous empty versus null lists. ADBC seeks to simplify deployment through TOML-based driver manifests and connection profiles, but it still has limitations in synchronous APIs, metadata support, and type coverage; planned specification improvements include multi-result sets, warning handlers, and application-requested type mappings. The presentation’s practical recommendations were to test schemas early, pin driver versions, and maintain clear visibility into the exact driver version in use.
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