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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

Description

DeviceHive is an open-source IoT data platform that offers extensive integration capabilities. Its varied deployment options make it suitable for organizations of any size, from established enterprises to emerging startups. With choices such as Docker Compose and Kubernetes, users can deploy in private, public, or hybrid cloud environments and can easily scale from a single virtual machine to a robust enterprise-level cluster. If you’re short on time for deployment, you can explore DeviceHive through our public playground without any setup. Whether you are in the prototyping phase or developing comprehensive enterprise solutions, taking a small step with DeviceHive can lead to significant advancements for your business. This platform enables you to prioritize business growth rather than getting bogged down in technical complexities. DeviceHive also follows top-tier software design principles, utilizing a container-based service-oriented architecture that is managed and orchestrated by Kubernetes, ensuring efficiency and adaptability. Embrace the future of IoT with DeviceHive and transform the way you approach your projects.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS App Mesh Yes 
AWS Lake Formation Yes 
AWS Step Functions Yes 
Apache Hive Yes 
Apache Phoenix Yes 
Feast Yes 
IBM watsonx.data integration Yes 
Immuta Yes 
Kubernetes No 
Lyftrondata Yes 
Okera Yes 
Pelanor Yes 
Prophecy Yes 
Quorso Yes 
SAS Studio Yes 
Tonic Ephemeral Yes 
TrustLogix Yes 
Veza Yes 
Zepl Yes 

Integrations

AWS App Mesh No 
AWS Lake Formation No 
AWS Step Functions No 
Apache Hive No 
Apache Phoenix No 
Feast No 
IBM watsonx.data integration No 
Immuta No 
Kubernetes Yes 
Lyftrondata No 
Okera No 
Pelanor No 
Prophecy No 
Quorso No 
SAS Studio No 
Tonic Ephemeral No 
TrustLogix No 
Veza No 
Zepl No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 No 
Live Rep (24/7) Yes 
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

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/emr/

Vendor Details

Company Name

DeviceHive

Founded

2012

Website

www.youtube.com/watch

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

IoT Analytics

Activity Dashboard No 
Activity Tracking No 
Analytics No 
Asset Tracking No 
Data Collection No 
Data Synchronization No 
Data Visualization No 
ETL No 
Multiple Data Sources No 
Performance Analysis No 
Real-Time Analytics No 
Real-Time Data No 
Real-Time Monitoring No 
Status Tracking No 

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