Skip to content

ADBC how-to guides

Each guide solves one specific task. For a continuous walkthrough see the tutorial; for the full supported surface see the reference.

Guides

Section titled “Guides”

Bulk-loading Parquet into XTDB via ADBC

Section titled “Bulk-loading Parquet into XTDB via ADBC”

pyarrow.parquet.read_table → cur.adbc_ingest. Schema requirements (the _id column), chunked ingest for tables larger than memory, error handling, and rejection modes.

Round-tripping pandas / polars DataFrames

Section titled “Round-tripping pandas / polars DataFrames”

Two directions:

  • Read XTDB into a pyarrow.Table and hand off to pandas / polars via to_pandas() / pl.from_arrow(), zero-copy where possible.
  • Build a DataFrame in pandas / polars, convert to Arrow, adbc_ingest it.

Covers type-fidelity preservation (categoricals, optional fields, timestamps with timezone).

Point-in-time feature extraction for ML training sets

Section titled “Point-in-time feature extraction for ML training sets”

Extract training-set features as known at label time: a single SQL query against FOR VALID_TIME AS OF produces a pyarrow.Table joined as-of label time, ready for a feature pipeline. It avoids training on information that wasn’t yet available at the label time, the mistake feature stores are built to prevent.

Streaming results into DuckDB

Section titled “Streaming results into DuckDB”

cur.fetch_arrow_table() → DuckDB register_arrow → join with DuckDB-resident data. When some of your data already lives in DuckDB, Arrow lets you join it against XTDB’s bitemporal data with no serialise/deserialise step between them.

Rust ADBC + arrow-rs pipeline

Section titled “Rust ADBC + arrow-rs pipeline”

End-to-end in Rust with adbc_core + arrow-rs: connect, ingest a RecordBatch, query, hand off to DataFusion for analytical compute, write the result out to Parquet. The Arrow types are checked at compile time through the whole pipeline.

Prepared statements and transactions

Section titled “Prepared statements and transactions”

The full prepared-statement lifecycle over the wire: prepare() once, bind() + executeQuery() many times, parameter binding via Arrow batches. Multi-statement transactions, autocommit on/off, rollback semantics, and how XTDB’s same-connection write-then-read works in practice.