databricks-sql
Databricks SQL framework, easy to learn, fast to code, ready for production.
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires valid Databricks credentials (access_token, http_path, server_hostname) and network access to a Databricks workspace.
- Low install friction with only 2 runtime dependencies.
- However, the package is abandoned—last release was 2022-12-18 with no commits since.
License · maintenance · safety
Apache 2-0 (permissive) — Licensed under Apache 2-0 (permissive), allowing commercial and private use with minimal restrictions.
last release 2022-12-18 (1335 days) · last repo commit 2022-12-18 · 2 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 92,954 downloads/mo, #13,412 on PyPI
Alternatives
Verify before relying
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()- 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
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 on this page. Verify before relying on it.
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
databricks-sql on PyPI
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.
Requires valid Databricks credentials (access_token, http_path, server_hostname) and network access to a Databricks workspace.
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()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 the current Python release >=3.8,<4.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesdatabricks-sql-connectorpystache |
| Maintenance | Abandoned 1,335 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 92,954 / month, #13,412 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: Other/Proprietary LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Database |
Evidence: databricks_sql-1.0.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “databricks query builder”
- databricks-sqlProvides a Python interface for querying and manipulating Databricks…
- databricks-dbapiProvides a DBAPI 2.0 connection interface and SQLAlchemy dialects to…
- sqlalchemy-databricksProvides a SQLAlchemy dialect that connects to Databricks workspaces…
Give your agent the search over MCP, or paste the wish link into any chat.
More Database packages
psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.
Python client library for connecting to and executing commands against Redis key-value stores, supporting both synchronous and asynchronous operations.
Install it if your application needs to interact with Redis; the only prerequisite is a running Redis server instance.
YDB Python SDK is the official client library for connecting to and querying YDB databases from Python applications.
Install it if you need to connect Python applications to YDB databases.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
sqlparse tokenizes SQL text into a tree of statements, clauses, and expressions, and provides functions to split scripts, format queries, and inspect parsed tokens without validating dialect or syntax.
Install it if you need to manipulate, format, or analyze SQL text programmatically.
Provides base adapter protocols and shared functionality that database adapters use to integrate with dbt-core, handling connections, dialect translation, relation caching, and core interface management.
See also databricks-labs-lsql · databricks-sql-connector · python-sql · sqlalchemy-databricks · databricks-sqlalchemy · databricks-labs-remorph · dbt-databricks · databricks-dbapi · dbl-discoverx · databricks-connect