Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Apache Mahout is an advanced and adaptable machine learning library that excels in processing distributed datasets efficiently. It encompasses a wide array of algorithms suitable for tasks such as classification, clustering, recommendation, and pattern mining. By integrating seamlessly with the Apache Hadoop ecosystem, Mahout utilizes MapReduce and Spark to facilitate the handling of extensive datasets. This library functions as a distributed linear algebra framework, along with a mathematically expressive Scala domain-specific language, which empowers mathematicians, statisticians, and data scientists to swiftly develop their own algorithms. While Apache Spark is the preferred built-in distributed backend, Mahout also allows for integration with other distributed systems. Matrix computations play a crucial role across numerous scientific and engineering disciplines, especially in machine learning, computer vision, and data analysis. Thus, Apache Mahout is specifically engineered to support large-scale data processing by harnessing the capabilities of both Hadoop and Spark, making it an essential tool for modern data-driven applications.
Description
Since its emergence in 2010, Hadoop has established itself as a crucial component of the data management ecosystem. Throughout the past decade, a significant number of organizations have embraced Hadoop to enhance their data lake frameworks. While Hadoop provided a budget-friendly option for storing vast quantities of data in a distributed manner, it also brought forth several complications. Operating these systems demanded specialized IT skills, and the limitations of on-premises setups hindered the ability to scale according to fluctuating usage requirements. The intricacies of managing these on-premises Hadoop configurations and the associated flexibility challenges are more effectively resolved through cloud solutions. To alleviate potential risks and costs tied to data modernization initiatives, numerous businesses have opted to streamline their cloud data migration processes with WANdisco. Their LiveData Migrator serves as a completely self-service tool, eliminating the need for any WANdisco expertise or support. This approach not only simplifies migration but also empowers organizations to handle their data transitions with greater efficiency.
API Access
Has API
Yes
API Access
Has API
No
Integrations
APERIO DataWise
No
Alibaba Cloud
No
Amazon Web Services (AWS)
No
Apache Spark
Yes
Databricks
No
Google Cloud Platform
No
Hadoop
Yes
IBM Cloud
No
Microsoft Azure
No
Oracle Cloud Infrastructure
No
Integrations
APERIO DataWise
Yes
Alibaba Cloud
Yes
Amazon Web Services (AWS)
Yes
Apache Spark
No
Databricks
Yes
Google Cloud Platform
Yes
Hadoop
No
IBM Cloud
Yes
Microsoft Azure
Yes
Oracle Cloud Infrastructure
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
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
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Apache Software Foundation
Country
United States
Website
mahout.apache.org
Vendor Details
Company Name
WANdisco
Founded
2005
Country
United States
Website
www.wandisco.com/use-cases/cloud-migration
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No