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What is DeviceHive?

DeviceHive serves as an open-source platform for IoT data, providing a wide range of integration options. Its flexible deployment strategies cater to organizations of all sizes, making it ideal for both large corporations and new startups. Users can choose deployment methods like Docker Compose and Kubernetes, allowing them to operate in private, public, or hybrid cloud settings and seamlessly scale from a single virtual machine to an expansive enterprise cluster. For those pressed for time, DeviceHive offers a public playground for exploration without the need for installation. Whether you are in the early stages of prototyping or working on extensive enterprise applications, a minor investment in DeviceHive can yield significant benefits for your organization. This platform empowers you to focus on business expansion rather than becoming overwhelmed by technical details. Moreover, DeviceHive adheres to high software design standards, employing a container-based, service-oriented architecture managed by Kubernetes, which guarantees both efficiency and adaptability. By choosing DeviceHive, you not only embrace the future of IoT but also revolutionize your approach to project execution and innovation. With its user-friendly features, DeviceHive is poised to enhance your IoT journey.

What is Apache Hive?

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

Media

Media

Integrations Supported

Aqua Data Studio
Astro by Astronomer
BigBI
Cloudera Data Warehouse
DataGrip
DreamFactory
E-MapReduce
IBM App Connect
IRI CoSort
IRI Data Protector Suite
Immuta
Microsoft Power Query
StarRocks
Truedat
Vaultspeed
Xtendlabs
Yandex Data Proc
e6data
eQube®-DaaS
jethro

Integrations Supported

Aqua Data Studio
Astro by Astronomer
BigBI
Cloudera Data Warehouse
DataGrip
DreamFactory
E-MapReduce
IBM App Connect
IRI CoSort
IRI Data Protector Suite
Immuta
Microsoft Power Query
StarRocks
Truedat
Vaultspeed
Xtendlabs
Yandex Data Proc
e6data
eQube®-DaaS
jethro

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

DeviceHive

Date Founded

2012

Company Website

www.youtube.com/watch

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and Features

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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