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Python

HBase Python Connector

Read, write, and update HBase with Python

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

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CData Drivers now work with AI Coding tools

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

Features

Accepts application SQL queries and generates execution plans
Connects to HBase REST Server 0.0.3, available in HBase version 0.98 and above
Maps ANSI SQL-92 to HBase REST API calls
Includes Apache Knox Gateway support
Connect to live Apache HBase data, for real-time data access with the Apache HBase ADO.NET Provider
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 HBase Connector.

Specifications

Python Database API (DB-API) Modules for HBase with bi-directional access.
Write SQL, get Apache HBase data. Access HBase through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
An easy-to-use 'flattened' interface for working with Apache HBase columnar databases.
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 Apache HBase

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


Connecting to HBase with Python

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


Connecting to HBase 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.apachehbase as mod
conn = mod.connect("[email protected]; Password=password;")

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

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

df.plot()
plt.show()

Visualize HBase Data with pandas

The data-centric interfaces of the HBase 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

HBase 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 HBase Connector as easily as interacting with a database table.

AI-assisted development with CData CLI

Build HBase integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your HBase 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 HBase.

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