Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Easily create and execute highly parallel data transformation and processing tasks using U-SQL, R, Python, and .NET across vast amounts of data. With no need to manage infrastructure, you can process data on demand, scale up instantly, and incur costs only per job. Azure Data Lake Analytics allows you to complete big data tasks in mere seconds. There’s no infrastructure to manage since there are no servers, virtual machines, or clusters that require monitoring or tuning. You can quickly adjust the processing capacity, measured in Azure Data Lake Analytics Units (AU), from one to thousands for every job. Payment is based solely on the processing used for each job. Take advantage of optimized data virtualization for your relational sources like Azure SQL Database and Azure Synapse Analytics. Your queries benefit from automatic optimization, as processing is performed close to the source data without requiring data movement, thereby enhancing performance and reducing latency. Additionally, this setup enables organizations to efficiently utilize their data resources and respond swiftly to analytical needs.
Description
Adaptive Data Virtualization™ technology empowers businesses to operate their current applications on contemporary cloud data warehouses without the need for extensive modifications or reconfiguration. With Datometry Hyper-Q™, organizations can swiftly embrace new cloud databases, effectively manage ongoing operational costs, and enhance their analytical capabilities to accelerate digital transformation efforts. This virtualization software from Datometry enables any existing application to function on any cloud database, thus facilitating interoperability between applications and databases. Consequently, enterprises can select their preferred cloud database without the necessity of dismantling, rewriting, or replacing their existing applications. Furthermore, it ensures runtime application compatibility by transforming and emulating legacy data warehouse functionalities. This solution can be deployed seamlessly on major cloud platforms like Azure, AWS, and GCP. Additionally, applications can leverage existing JDBC, ODBC, and native connectors without any alterations, ensuring a smooth transition. It also establishes connections with leading cloud data warehouses, including Azure Synapse Analytics, AWS Redshift, and Google BigQuery, broadening the scope for data integration and analysis.
API Access
Has API
No
API Access
Has API
No
Integrations
Microsoft Azure
Yes
Amazon Redshift
No
Amazon Web Services (AWS)
No
Azure Data Lake
Yes
Azure Synapse Analytics
No
Cognizant
No
DXC Cloud
No
Google Cloud BigQuery
No
Google Cloud Platform
No
Microsoft 365
No
Integrations
Microsoft Azure
Yes
Amazon Redshift
Yes
Amazon Web Services (AWS)
Yes
Azure Data Lake
No
Azure Synapse Analytics
Yes
Cognizant
Yes
DXC Cloud
Yes
Google Cloud BigQuery
Yes
Google Cloud Platform
Yes
Microsoft 365
Yes
Pricing Details
$2 per hour
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
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
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
No
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
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/data-lake-analytics/
Vendor Details
Company Name
Datometry
Founded
2013
Country
United States
Website
datometry.com/products/database-migration/
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Product Features
Virtualization
Archiving & Retention
No
Capacity Monitoring
No
Data Mobility
No
Desktop Virtualization
No
Disaster Recovery
No
Namespace Management
No
Performance Management
No
Version Control
No
Virtual Machine Monitoring
No