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Python

Amazon DynamoDB Python Connector

Read, write, and update Amazon DynamoDB with Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Amazon DynamoDB!

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

Features

Perform value-sensitive queries that properly interface with the loose typing available in DynamoDB columns
Easily insert and update entire DynamoDB documents and lists
Compatible with the current version of the DynamoDB REST API, version 2012-08-10
Makes use of DynamoDB indexing for improved performance
Enables SQL-92 capabilities on Amazon DynamoDB NoSQL data.
Flexible NoSQL flattening - automatic schema generation, flexible querying etc.
Connect to live Amazon DynamoDB data, for real-time data access with the Amazon DynamoDB JDBC Driver
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 via the Amazon DynamoDB Connector.

Specifications

Python Database API (DB-API) Modules for Amazon DynamoDB with bi-directional access.
Write SQL, get Amazon DynamoDB data. Access Amazon DynamoDB through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Simple command-line based data exploration of Amazon DynamoDB always-on real-time cloud data storage.
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 Amazon DynamoDB

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


Connecting to Amazon DynamoDB with Python

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


Connecting to Amazon DynamoDB in Python

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

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.

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

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Account")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("amazondynamodb///Password=password&User=user")

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

df.plot()
plt.show()

Visualize Amazon DynamoDB Data with pandas

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

More than read-only: full update/CRUD support

Amazon DynamoDB 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 Amazon DynamoDB Connector as easily as interacting with a database table.

AI-assisted development with CData CLI

Build Amazon DynamoDB integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Amazon DynamoDB schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Amazon DynamoDB.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI