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Description
IBM Analytics for Apache Spark offers a versatile and cohesive Spark service that enables data scientists to tackle ambitious and complex inquiries while accelerating the achievement of business outcomes. This user-friendly, continually available managed service comes without long-term commitments or risks, allowing for immediate exploration. Enjoy the advantages of Apache Spark without vendor lock-in, supported by IBM's dedication to open-source technologies and extensive enterprise experience. With integrated Notebooks serving as a connector, the process of coding and analytics becomes more efficient, enabling you to focus more on delivering results and fostering innovation. Additionally, this managed Apache Spark service provides straightforward access to powerful machine learning libraries, alleviating the challenges, time investment, and risks traditionally associated with independently managing a Spark cluster. As a result, teams can prioritize their analytical goals and enhance their productivity significantly.
Description
Oracle Cloud Infrastructure (OCI) Data Flow is a comprehensive managed service for Apache Spark, enabling users to execute processing tasks on enormous data sets without the burden of deploying or managing infrastructure. This capability accelerates the delivery of applications, allowing developers to concentrate on building their apps rather than dealing with infrastructure concerns. OCI Data Flow autonomously manages the provisioning of infrastructure, network configurations, and dismantling after Spark jobs finish. It also oversees storage and security, significantly reducing the effort needed to create and maintain Spark applications for large-scale data analysis. Furthermore, with OCI Data Flow, there are no clusters that require installation, patching, or upgrading, which translates to both time savings and reduced operational expenses for various projects. Each Spark job is executed using private dedicated resources, which removes the necessity for prior capacity planning. Consequently, organizations benefit from a pay-as-you-go model, only incurring costs for the infrastructure resources utilized during the execution of Spark jobs. This innovative approach not only streamlines the process but also enhances scalability and flexibility for data-driven applications.
API Access
Has API
API Access
Has API
Integrations
Apache Spark
Oracle Cloud Infrastructure
RadiantOne
Switch Automation
Integrations
Apache Spark
Oracle Cloud Infrastructure
RadiantOne
Switch Automation
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$0.0085 per GB per hour
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/analytics/ca/en/technology/cloud-data-services/spark-as-a-service/
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/big-data/data-flow/
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports