---
id: databricks-sql
version: "1.0.0"
license: Apache 2-0
license_treatment: permissive
maintenance: abandoned
---

# databricks-sql — Databricks SQL framework, easy to learn, fast to code, ready for production.

License: permissive · Maintenance: abandoned · Downloads: 93.0K/mo

## What it is and what it does

databricks-sql is a lightweight Python wrapper that exposes Databricks SQL operations through a fluent, chainable API. Instead of writing raw SQL strings, you build queries using methods like .select(), .insert(), .update(), and .delete(), chaining conditions with .where() and .set() before calling .execute(). It also supports mustache templating for conditional SQL fragments.

The package depends on databricks-sql-connector for the actual connection and pystache for template rendering. It is designed for Python 3.8 through 3.11 and works with Databricks' three-tier namespace (catalog.schema.table). However, the project has been abandoned since 2022-12-18 with no maintenance activity since then, carrying the risk of incompatibility with newer Databricks API changes.

Use it for:

- Build parameterized delete queries with WHERE conditions without writing raw SQL strings
- Insert rows into Databricks tables by chaining .set() calls instead of constructing INSERT statements
- Execute SELECT queries with optional filtering, ordering, and pagination using a fluent interface
- Load and render SQL templates from files with mustache syntax for conditional query fragments
- Update table rows with multiple field assignments and complex WHERE conditions in a readable chain

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides a Python interface for querying and manipulating Databricks SQL tables with chainable methods for select, insert, update, and delete operations.

No. The package is abandoned (last release 2022-12-18, no commits since) and carries maintenance risk. While install friction is low and the Apache 2-0 license is permissive, the frozen codebase may not work with current Databricks infrastructure. Consider using databricks-sql-connector directly or a maintained alternative unless you are certain the 1.0.0 API is stable for your use case.

## Install

pip install databricks-sql
uv add databricks-sql
poetry add databricks-sql

## Installing databricks-sql

Before you install: Low install friction with only 2 runtime dependencies. However, the package is abandoned—last release was 2022-12-18 with no commits since. Use only if you are confident the frozen API meets your needs.

License in practice: Licensed under Apache 2-0 (permissive), allowing commercial and private use with minimal restrictions.

Quickstart:

pip install databricks-sql

from databricks_sql.client import Configuration, Database

CONFIGURATION = Configuration.instance(
    access_token="",
    command_directory="",
    http_path="",
    server_hostname="",
)

with Database() as connection:
    connection.select("catalog.schema.table").execute().fetch_all()

Requires valid Databricks credentials (access_token, http_path, server_hostname) and network access to a Databricks workspace.

Verify before relying:

- Whether databricks-sql-connector and pystache versions are compatible with current Databricks infrastructure
- Whether Configuration.instance() requires all four parameters or if some have defaults
- Whether the package handles connection pooling or concurrent queries

## Package facts

- License: Apache 2-0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: abandoned
- Downloads: 93.0K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

databricks sql client, databricks query builder, databricks table operations, sql query builder python, databricks connector, databricks delete insert update, fluent sql interface, query-builder, abandoned

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