How to use VAST DataBase from each client and engine. Start with Python SDK if you write Python, or Trino or Spark if you use those engines; VAST Query Engine (ADBC) covers SQL on the cluster itself, and Arrow, pandas and Polars covers dataframes.
- Python SDK: How the vastdb SDK's objects fit together, with idioms for create-or-get, transactions, metadata reuse, configuration, retries, threads and tests.
- Trino: Use VAST DataBase as a Trino catalog: catalog properties, name mapping, partitioned and sorted tables, pushdown, EXPLAIN and row and column security.
- Spark: Use the ndb catalog from Spark SQL and PySpark: connector properties, name mapping, partitioned and sorted tables, views and row security.
- VAST Query Engine (ADBC): Run SQL in the VAST Query Engine through the ADBC driver, standalone or inside a Python SDK transaction, and impersonate end users.
- Arrow, pandas and Polars: Move data between VAST DataBase and pandas, Polars, DuckDB and Parquet through Arrow, and watch for type conversions on insert.