Anaplan Python Connector

SQL-based Access to Anaplan from Python

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

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

Features

Enables SQL-92 capabilities on Anaplan NoSQL data.
Flexible NoSQL flattening - automatic schema generation, flexible querying etc.
Powerful metadata querying enables SQL-like access to non-database sources
Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
Client-side query execution engine, supports SQL-92 operations that are not available server-side
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Anaplan Connector.

Specifications

Python Database API (DB-API) Modules for Anaplan .
Write SQL, get Anaplan data. Access Anaplan 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 Anaplan

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

Universal Python Anaplan Connectivity
Easily connect to Anaplan 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 Anaplan 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 Anaplan 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 Anaplan 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 Anaplan 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 Anaplan with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Anaplan 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 Anaplan
Query Anaplan to retrieve or update data
Connect your Anaplan data with Python data tools.

Connecting to Anaplan in Python

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

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

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Exports")
 
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 Anaplan Data with pandas

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

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

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

df.plot()
plt.show()

AI-Assisted Development with CData MCP Server

Build Anaplan integrations faster with AI that understands your schema

Supported AI Coding Tools

Schema-Aware AI

MCP Server gives AI coding tools direct access to your Anaplan schema. No more guessing table names or column types—AI sees the same metadata as your Python Connector.

Same Schema, Same SQL

Table names, column names, and SQL syntax in MCP Server are identical to this Python Connector. Queries you validate with AI work directly in your production code.

From Prototype to Production

Stop guessing. Start shipping. Prototype queries in conversation, validate against live data, then deploy with CData Python Connectors—no rewriting required.

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Free for development. No trial period. No credit card required.