A lightweight Python framework to bridge the gap between complex data warehouses and actionable analytics. Open-source, modular, and fast.
pip install db-analytics-tools
DB Analytics Tools was born from a simple observation: modern data stacks are often too heavy for agile teams who need to move fast. Our framework focuses on the essentials: connectivity, extraction, and transformation.
Whether you are working with PostgreSQL, MySQL, or cloud data warehouses, we provide a unified interface that eliminates boilerplate code and lets you focus on the logic of your data.
Scheduled extractions without the headache.
Robust secret management integrated.
Stop wasting time with complex boilerplate. Connect and query in seconds.
import db_analytics_tools as db client = db.Client( host=HOST, port=PORT, database=DATABASE, username=USER, password=PASSWORD, engine=ENGINE )
Supports PostgreSQL, Greenplum and SQL Server.
Modular architecture designed to handle every step of your data pipeline.
A high-level wrapper around SQL engines. Execute queries, manage sessions, and retrieve DataFrames with a single method call.
Automate the flow of data. Built-in functions for incremental loads, streaming extraction, and schema management.
Turn raw data into insights. Integration with top charting libraries to generate professional reports directly from your datasets.
Standardized machine learning workflows. Simplified training, evaluation, and deployment of models within your data ecosystem.
Native Airflow integration. Orchestrate your tasks with ease using our custom operators and REST API wrappers.
A ready-to-use administration console built with Streamlit to monitor your pipelines and visualize your database health.
Choose the right path for your project or organization.
Perfect for individual contributors, researchers, and small open-source projects.
Tailored solutions for teams requiring priority support and specialized services.
Your support helps us maintain the core library, improve documentation, and develop new connectors.