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
Cazena's Instant Data Lake significantly reduces the time needed for analytics and AI/ML from several months to just a few minutes. Utilizing its unique automated data platform, Cazena introduces a pioneering SaaS model for data lakes, requiring no operational input from users. Businesses today seek a data lake that can seamlessly accommodate all their data and essential tools for analytics, machine learning, and artificial intelligence. For a data lake to be truly effective, it must ensure secure data ingestion, provide adaptable data storage, manage access and identities, facilitate integration with various tools, and optimize performance among other features. Building cloud data lakes independently can be quite complex and typically necessitates costly specialized teams. Cazena's Instant Cloud Data Lakes are not only designed to be readily operational for data loading and analytics but also come with a fully automated setup. Supported by Cazena’s SaaS Platform, they offer ongoing operational support and self-service access through the user-friendly Cazena SaaS Console. With Cazena's Instant Data Lakes, users have a completely turnkey solution that is primed for secure data ingestion, efficient storage, and comprehensive analytics capabilities, making it an invaluable resource for enterprises looking to harness their data effectively and swiftly.
API Access
Has API
No
API Access
Has API
No
Integrations
Microsoft Azure
Yes
AWS IoT SiteWise
No
Amazon Web Services (AWS)
No
Azure Data Lake
Yes
Cloudera
No
Openbridge
Yes
Privacera
No
Integrations
Microsoft Azure
Yes
AWS IoT SiteWise
Yes
Amazon Web Services (AWS)
Yes
Azure Data Lake
No
Cloudera
Yes
Openbridge
No
Privacera
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
Yes
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
No
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
Cazena
Founded
2015
Country
United States
Website
cazena.com
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
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