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EnterpriseDB Python Connector
 

EnterpriseDB Python Connector

Read, Write, and Update EnterpriseDB with Python

Easily connect Python-based Data Access, Visualization, ORM, ETL, AI/ML, and Custom Apps with EnterpriseDB!


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Python Connector Libraries for EnterpriseDB Data Connectivity. Integrate EnterpriseDB with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect EnterpriseDB data with Python and any Python-based applications.

Features

  • Fully compatible with Enterprise DB 12 and later
  • Connect to live EnterpriseDB data, for real-time data access
  • Full support for data aggregation and complex JOINs in SQL queries
  • Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
  • Seamless integration with leading BI, reporting, and ETL tools and with custom applications

Specifications

  • Python Database API (DB-API) Modules for EnterpriseDB with bi-directional access.
  • Write SQL, get EnterpriseDB data. Access EnterpriseDB through standard Python Database Connectivity.
  • Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
  • Full Unicode support for data, parameter, & metadata.


CData 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 PYTHON CONNECTOR VIDEO OVERVIEW

Python Connectivity with EnterpriseDB

Full-featured and consistent SQL access to any supported data source through Python


  • Universal Python EnterpriseDB Connectivity

    Easily connect to EnterpriseDB 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

    The EnterpriseDB Connector integrates seamlessly with popular data science and developer tooling like Anaconda, Visual Studio Python IDE, PyCharm, and more. Real Python,

  • 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 EnterpriseDB Connector includes 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 Connector enhances the capabilities of EnterpriseDB with 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 EnterpriseDB Connector 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 to EnterpriseDB with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with EnterpriseDB from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to EnterpriseDB
  • Query EnterpriseDB to retrieve or update data
  • Connect your EnterpriseDB data with Python data tools.


Connecting to EnterpriseDB in Python

To connect to your data from Python, import the extension and create a connection:

import cdata.enterprisedb as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM EnterpriseDBTable")
 
rs = cur.fetchall()
 
for row in rs:
print(row)

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

Visualize EnterpriseDB Data with pandas

The data-centric interfaces of the EnterpriseDB Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time. 

engine = create_engine("enterprisedb///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM EnterpriseDBTable", engine)

df.plot()
plt.show()

More Than Read-Only: Full Update/CRUD Support

EnterpriseDB Connector goes beyond read-only functionality to deliver full support for Create, Read Update, and Delete operations (CRUD). Your end-users can interact with the data presented by the EnterpriseDB Connector as easily as interacting with a database table.

Popular Python Videos:

Python Connectors, Jupyter Notebook, and pandas