Python Connectors
Connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with data from anywhere!
- Database API (DB-API) Modules for SaaS, Big Data, and NoSQL
- Supports popular tools like pandas, SQLAlchemy, Dash, & petl
- Simple command-line based data exploration
Universal Python data connectivity
Easy-to-use Python Database API (DB-API) Modules for data connectivity. Straightforward access to live application, database, and cloud API data through standard Python database connectivity.
Seamless integration with popular data science tooling, like pandas, SQLAlchemy, Dash, & petl.
Developers can use our Python Connectors to rapidly connect Web, Desktop, and Mobile apps to data.
Built with the same reliability, scalability, performance & security powering leading data integration solutions.
A robust SQL-engine simplifies data movement & processing from Cloud Apps, NoSQL, Files, & more.
Python Connectors
Python Database API (DB-API) Modules for NoSQL, Big Data, & SaaS Integration.
(API Driver)
Python connectors in action!
Watch the video overview for a first-hand look at the powerful data integration capabilities included in the CData Python Connectors.
Watch the Video
Powerful enterprise-class data connectivity features
Full-featured and consistent SQL access to any supported data source from Python
Universal Python Data Connectivity
Easily connect with SaaS, Big Data, and NoSQL data from common Python-based frameworks, including:
- Data Analysis/Visualization: Jupyter Notebook, pandas, Matplotlib
- ORM: SQLAlchemy, SQLObject, Storm
- Web Applications: Dash, Django
- ETL: Apache Airflow, Luigi, Bonobo, Bubbles, petl
Popular Tooling Integration
All of our Python Connectors integrate seamlessly with popular data science and developer tooling like Anaconda, Visual Studio Python IDE, PyCharm, Real Python, and more.
Replication and Caching
Our replication and caching commands make it easy to copy data to local and cloud data stores such as Oracle, SQL Server, Google Cloud SQL, etc. The replication commands include many features that allow for intelligent incremental updates to cached data.
String, Date, Numeric SQL Functions
The Python Connectors include a library of 50 plus functions that can manipulate column values into the desired result. Popular examples include Regex, JSON, and XML processing functions.
Collaborative Query Processing
Our Python Connectors enhance the data source's capabilities by additional client-side processing, when needed, to enable analytic summaries of data such as SUM, AVG, MAX, MIN, etc.
Easily Customizable and Configurable
The data model exposed by our Python Connectors can easily be customized to add or remove tables/columns, change data types, etc. without requiring a new build. These customizations are supported at runtime using human-readable schema files that are easy to edit.
Enterprise-class Secure Connectivity
Includes standard Enterprise-class security features such as TLS/ SSL data encryption for all client-server communications.
Connecting Python with data from anywhere
Support DataOps with easy-to-use data-centric connectors
Organizations worldwide are using Python to harvest insights from data. Python's vast ecosystem of tools, modules, and extensions support DataOps initiatives by dramatically simplifying data movement and processing.
The CData Python Connectors fill a critical gap in Python tooling by providing consistent connectivity with data-centric interfaces to hundreds of different SaaS/Cloud, NoSQL, and Big Data sources.
CData Python connectors in action
Use python-based tools like pandas, SQLAlchemy, & Matplotlib for Salesforce data analysis and reporting.
Leverage SQLAlchemy Object-Relational Mapping for Jira integration from Python.
Build Snowflake-powered web apps with CData Snowflake Connector, pandas, and Dash.
Create simple command-line ETL Pipelines with CData NetSuite Python Connector and petl.
