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What is Oracle Big Data Service?

Oracle Big Data Service makes it easy for customers to deploy Hadoop clusters by providing a variety of virtual machine configurations, from single OCPUs to dedicated bare metal options. Users have the choice between high-performance NVMe storage and more economical block storage, along with the ability to scale their clusters according to their requirements. This service enables the rapid creation of Hadoop-based data lakes that can either enhance or supplement existing data warehouses, ensuring that data remains both accessible and well-managed. Users can efficiently query, visualize, and transform their data, facilitating data scientists in building machine learning models using an integrated notebook that accommodates R, Python, and SQL. Additionally, the platform supports the conversion of customer-managed Hadoop clusters into a fully-managed cloud service, which reduces management costs and enhances resource utilization, thereby streamlining operations for businesses of varying sizes. By leveraging this service, companies can dedicate more time to extracting valuable insights from their data rather than grappling with the intricacies of managing their clusters. This ultimately leads to more efficient data-driven decision-making processes.

What is Azure Data Lake Analytics?

Easily construct and implement highly parallelized data transformation and processing tasks using U-SQL, R, Python, and .NET across extensive datasets. There’s no requirement to manage any infrastructure, allowing you to process data on demand, scale up in an instant, and pay only for completed jobs. Harness the power of Azure Data Lake Analytics to perform large-scale data operations in just seconds. You won’t have to worry about server management, virtual machines, or clusters that need maintenance or fine-tuning. With Azure Data Lake Analytics, you can rapidly adjust processing capabilities, measured in Azure Data Lake Analytics Units (AU), from a single unit to thousands for each job as needed. You are billed solely for the processing power used during each task. The optimized data virtualization of your relational sources, such as Azure SQL Database and Azure Synapse Analytics, allows you to interact with all your data seamlessly. Your queries benefit from automatic optimization, which brings processing closer to where the original data resides, consequently minimizing data movement, boosting performance, and reducing latency. This capability ensures that you can tackle even the most challenging data tasks with exceptional efficiency and speed, ultimately transforming the way you handle data analytics.

Media

Media

Integrations Supported

Azure Data Lake
Hadoop
Microsoft Azure
Openbridge
Oracle Cloud Infrastructure

Integrations Supported

Azure Data Lake
Hadoop
Microsoft Azure
Openbridge
Oracle Cloud Infrastructure

API Availability

Has API

API Availability

Has API

Pricing Information

$0.1344 per hour
Free Trial Offered?
Free Version

Pricing Information

$2 per hour
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

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/big-data/big-data-service/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/data-lake-analytics/

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

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