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ClickhouseAnnouncement
One Driver, One Format, Every Language: ADBC
Summary
ClickHouse announces an official ADBC driver, a modern Arrow-native alternative to ODBC and JDBC for analytics and AI applications. It provides end-to-end columnar movement: query results leave ClickHouse as Apache Arrow and arrive in applications without a row-oriented conversion or staging step. A single Rust-built implementation connects through ClickHouse's HTTP interface, supports TLS, and serves languages and tools with ADBC bindings, including Ruby, R, and C. Users can install precompiled, signed binaries through the ADBC Driver Foundry and connect with a clickhouse:// URI; dbt Fusion distributes the driver directly. The driver also supports streaming Arrow inserts, while schema discovery, improved bulk ingest, usage examples, and JSON support remain on the roadmap.
Context
ODBC and JDBC use row-oriented connectivity, which can force ClickHouse query results through conversions before applications reconstruct them as columnar data. ADBC is intended for the columnar workflows used by modern analytics tools, and it provides database access for languages such as Ruby, R, and C that do not have official ClickHouse clients.
Approach / What changed
The driver implements the ADBC standard in Rust and connects to ClickHouse through its HTTP interface, with TLS supported out of the box. It keeps query results in Apache Arrow from ClickHouse to the application, supports Arrow record batches and streaming inserts, and uses clickhouse:// URIs with the ADBC driver manager. Precompiled, signed binaries are distributed through the ADBC Driver Foundry.
Takeaways
The driver returns ClickHouse query results as Apache Arrow record batches, allowing pandas and Polars workflows to receive columnar data without a conversion step.
A single Rust implementation supports every language and tool with ADBC bindings, extending ClickHouse access to Ruby, R, and C without separate language-specific drivers.
Arrow streaming inserts can write batches to an existing ClickHouse table with memory usage that remains flat regardless of data volume; automatic table creation is planned for a future release.
Source and freshness
- Source
- clickhouse.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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