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features
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support

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Description

A data lake serves as a comprehensive repository designed for handling extensive data and artificial intelligence operations, accommodating both structured and unstructured data at any volume. It is essential for organizations looking to harness the power of Data Lake Formation (DLF), which simplifies the creation of a cloud-native data lake environment. DLF integrates effortlessly with various computing frameworks while enabling centralized management of metadata and robust enterprise-level permission controls. It systematically gathers structured, semi-structured, and unstructured data, ensuring substantial storage capabilities, and employs a design that decouples computing resources from storage solutions. This architecture allows for on-demand resource planning at minimal costs, significantly enhancing data processing efficiency to adapt to swiftly evolving business needs. Furthermore, DLF is capable of automatically discovering and consolidating metadata from multiple sources, effectively addressing issues related to data silos. Ultimately, this functionality streamlines data management, making it easier for organizations to leverage their data assets.

Description

Utilize Azure Table storage to manage petabytes of semi-structured data efficiently while keeping expenses low. In contrast to various data storage solutions, whether local or cloud-based, Table storage enables seamless scaling without the need for manual sharding of your dataset. Additionally, concerns about data availability are mitigated through the use of geo-redundant storage, which ensures that data is replicated three times within a single region and an extra three times in a distant region, enhancing data resilience. This storage option is particularly advantageous for accommodating flexible datasets—such as user data from web applications, address books, device details, and various other types of metadata—allowing you to develop cloud applications without restricting the data model to specific schemas. Each row in a single table can possess a unique structure, for instance, featuring order details in one entry and customer data in another, which grants you the flexibility to adapt your application and modify the table schema without requiring downtime. Furthermore, Table storage is designed with a robust consistency model to ensure reliable data access. Overall, it provides an adaptable and scalable solution for modern data management needs.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Yes 
Auth.js No 
Autymate No 
DQ Studio No 
Data Sentinel No 
Microsoft Azure No 
NXLog No 
SSIS Integration Toolkit No 
StarfishETL No 

Integrations

Alibaba Cloud No 
Auth.js Yes 
Autymate Yes 
DQ Studio Yes 
Data Sentinel Yes 
Microsoft Azure Yes 
NXLog Yes 
SSIS Integration Toolkit Yes 
StarfishETL Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Alibaba Cloud

Founded

2008

Country

China

Website

www.alibabacloud.com/es/product/datalake-formation

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

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

Product Features

Product Features

NoSQL Database

Auto-sharding No 
Automatic Database Replication No 
Data Model Flexibility No 
Deployment Flexibility No 
Dynamic Schemas No 
Integrated Caching No 
Multi-Model No 
Performance Management No 
Security Management No 

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