---
title: "Integrations"
slug: "dev-database-integrations"
updated: 2026-11-05T22:16:11Z
published: 2026-11-05T22:16:11Z
canonical: "docs.vastdata.com/dev-database-integrations"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vastdata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Integrations

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](/develop/docs/dev-database-integrations-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](/develop/docs/dev-database-integrations-trino)**: Use VAST DataBase as a Trino catalog: catalog properties, name mapping, partitioned and sorted tables, pushdown, EXPLAIN and row and column security.
- **[Spark](/develop/docs/dev-database-integrations-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)](/develop/docs/dev-database-integrations-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](/develop/docs/dev-database-integrations-arrow-pandas-polars)**: Move data between VAST DataBase and pandas, Polars, DuckDB and Parquet through Arrow, and watch for type conversions on insert.