Amazon EMR

Amazon EMR

Amazon
Apache Mahout

Apache Mahout

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation

About

Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting.

About

Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark.

About

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

About

JavaScript is a scripting language and programming language for the web that enables developers to build dynamic elements on the web. Over 97% of the websites in the world use client-side JavaScript. JavaScript is one of the most important scripting languages on the web. Strings in JavaScript are contained within a pair of either single quotation marks '' or double quotation marks "". Both quotes represent Strings but be sure to choose one and STICK WITH IT. If you start with a single quote, you need to end with a single quote. There are pros and cons to using both IE single quotes tend to make it easier to write HTML within Javascript as you don’t have to escape the line with a double quote. Let’s say you’re trying to use quotation marks inside a string. You’ll need to use opposite quotation marks inside and outside of JavaScript single or double quotes.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies that want to easily run and scale Apache Spark, Hive, Presto, and other big data frameworks

Audience

Individuals requiring a tool for creating scalable performant machine learning applications

Audience

Organizations that want a unified analytics engine for large-scale data processing

Audience

Web developers and anyone looking for a mobile solution for running and developing web content

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/emr/

Company Information

Apache Software Foundation
United States
mahout.apache.org

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org

Company Information

JavaScript
Founded: 1995
United States
javascript.com

Alternatives

Alternatives

MLlib

MLlib

Apache Software Foundation

Alternatives

dbt

dbt

dbt Labs

Alternatives

Apache Spark

Apache Spark

Apache Software Foundation
AWS Glue

AWS Glue

Amazon
AssemblyScript

AssemblyScript

The AssemblyScript Project
E-MapReduce

E-MapReduce

Alibaba
E-MapReduce

E-MapReduce

Alibaba
MLlib

MLlib

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation

Categories

Categories

Categories

Categories

Streaming Analytics Features

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Integrations

CudaText
EC2 Spot
IPQS Device Fingerprinting
Inspectle
InstaWebAI
Komodo Edit
Latenode
Mage Dynamic Data Masking
Makedraft
Mobissue
Pavilion HyperOS
Phylum
Red Hat Runtimes
Restack
RunCode
ScrapingAnt
Sonatype Nexus Repository
Stirdie
Tonic Ephemeral
Toolaska

Integrations

CudaText
EC2 Spot
IPQS Device Fingerprinting
Inspectle
InstaWebAI
Komodo Edit
Latenode
Mage Dynamic Data Masking
Makedraft
Mobissue
Pavilion HyperOS
Phylum
Red Hat Runtimes
Restack
RunCode
ScrapingAnt
Sonatype Nexus Repository
Stirdie
Tonic Ephemeral
Toolaska

Integrations

CudaText
EC2 Spot
IPQS Device Fingerprinting
Inspectle
InstaWebAI
Komodo Edit
Latenode
Mage Dynamic Data Masking
Makedraft
Mobissue
Pavilion HyperOS
Phylum
Red Hat Runtimes
Restack
RunCode
ScrapingAnt
Sonatype Nexus Repository
Stirdie
Tonic Ephemeral
Toolaska

Integrations

CudaText
EC2 Spot
IPQS Device Fingerprinting
Inspectle
InstaWebAI
Komodo Edit
Latenode
Mage Dynamic Data Masking
Makedraft
Mobissue
Pavilion HyperOS
Phylum
Red Hat Runtimes
Restack
RunCode
ScrapingAnt
Sonatype Nexus Repository
Stirdie
Tonic Ephemeral
Toolaska
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