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What is Azure Table Storage?

Leverage Azure Table storage for the efficient management of large volumes of semi-structured data while keeping costs low. Unlike other data storage options, whether they are hosted on-site or in the cloud, Table storage offers effortless scalability, eliminating the need for any manual dataset sharding. Additionally, worries about data availability are alleviated thanks to geo-redundant storage, which ensures that your information is duplicated three times within a single region and another three times in a distant region. This service is particularly beneficial for a variety of datasets, including user information from online platforms, contacts, device specifications, and assorted metadata, empowering you to develop cloud applications without being tied to rigid data schemas. Different rows can have unique structures within the same table—such as one row containing order information and another holding customer details—granting you the flexibility to modify your application and table schema without experiencing downtime. Furthermore, Azure Table storage maintains a strong consistency model, which guarantees dependable data access and integrity. This makes it an excellent option for enterprises aiming to effectively manage evolving data needs, while also providing the opportunity for seamless integration with other Azure services.

What is Apache HBase?

When you need immediate and random read/write capabilities for large datasets, Apache HBaseâ„¢ is a solid option to consider. This project specializes in handling enormous tables that can consist of billions of rows and millions of columns across clusters made of standard hardware. It includes automatic failover functionalities among RegionServers to guarantee continuous operation without interruptions. In addition, it features a straightforward Java API for client interaction, simplifying the process for developers. There is also a Thrift gateway and a RESTful Web service available, which supports a variety of data encoding formats, such as XML, Protobuf, and binary. Moreover, it allows for the export of metrics through the Hadoop metrics subsystem, which can integrate with files or Ganglia, or even utilize JMX for improved monitoring. This adaptability positions it as a robust solution for organizations with significant data management requirements, making it a preferred choice for those looking to optimize their data handling processes.

Media

Media

Integrations Supported

Data Sentinel
Apache PredictionIO
Apache Zeppelin
Auth.js
DQ Studio
DigDash
FF4J
Hackolade
Hue
IRI DarkShield
Lyftrondata
MLlib
Mage Sensitive Data Discovery
Mage Static Data Masking
NXLog
Salesforce Data 360
StarfishETL
Toad Intelligence Central
WINDEV
Yandex Data Proc

Integrations Supported

Data Sentinel
Apache PredictionIO
Apache Zeppelin
Auth.js
DQ Studio
DigDash
FF4J
Hackolade
Hue
IRI DarkShield
Lyftrondata
MLlib
Mage Sensitive Data Discovery
Mage Static Data Masking
NXLog
Salesforce Data 360
StarfishETL
Toad Intelligence Central
WINDEV
Yandex Data Proc

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/storage/tables/#features

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hbase.apache.org

Categories and Features

NoSQL Database

Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management

Categories and Features

NoSQL Database

Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management

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