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Azure IoT Hub VS Apache Hive

Compare Azure IoT Hub VS Apache Hive and see what are their differences

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Azure IoT Hub logo Azure IoT Hub

Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.

Apache Hive logo Apache Hive

Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
  • Azure IoT Hub Landing page
    Landing page //
    2023-03-25
  • Apache Hive Landing page
    Landing page //
    2023-01-13

Azure IoT Hub features and specs

  • Scalability
    Azure IoT Hub can handle millions of simultaneously connected devices, making it highly scalable for large IoT deployments.
  • Integration with Microsoft Azure
    It integrates seamlessly with other Azure services like Azure Stream Analytics, Azure Machine Learning, and Azure Blob Storage, providing a comprehensive solution for IoT applications.
  • Security Features
    Azure IoT Hub offers robust security features, including device authentication, per-device identity, and secure data transfer, ensuring a high level of security for IoT solutions.
  • Bi-Directional Communication
    Supports bi-directional communication between devices and the cloud, allowing for immediate feedback and control.
  • Device Management
    Provides extensive device management capabilities, such as provisioning, configuration, and firmware updates, which simplifies managing a large number of devices.
  • Real-Time Data Ingestion
    Allows for real-time data ingestion and processing, which is critical for time-sensitive IoT applications.

Possible disadvantages of Azure IoT Hub

  • Complexity
    The extensive set of features and customizations can make the initial setup and onboarding process complex and time-consuming.
  • Cost
    Can be costly for small-scale deployments, especially if you are leveraging multiple Azure services in conjunction with IoT Hub.
  • Learning Curve
    Requires a steep learning curve for developers who are not already familiar with Microsoft Azure and its ecosystem.
  • Dependence on Other Azure Services
    While integration with other Azure services is a pro, it can also be a con as it may necessitate additional services and expenses.
  • Geographical Limitations
    Some services and features may not be available in all geographical regions, which could limit functionality based on location.
  • Latency
    While generally low, latency could be an issue depending on the geographical distance between the IoT devices and the Azure data centers.

Apache Hive features and specs

  • Scalability
    Apache Hive is built on top of Hadoop, allowing it to efficiently handle large datasets by distributing the load across a cluster of machines.
  • SQL-like Interface
    Hive provides a familiar SQL-like querying language, HiveQL, which makes it easier for users with SQL knowledge to perform data analysis on large datasets without needing to learn a new syntax.
  • Integration with Hadoop Ecosystem
    Hive integrates seamlessly with other components of the Hadoop ecosystem such as HDFS for storage and MapReduce for processing, making it a versatile tool for big data processing.
  • Schema on Read
    Hive uses a schema-on-read model which allows it to work with flexible data schemas and handle unstructured or semi-structured data efficiently.
  • Extensibility
    Users can extend Hive's capabilities by writing custom UDFs (User Defined Functions), UDAFs (User Defined Aggregate Functions), and SerDes (Serializers/ Deserializers).

Possible disadvantages of Apache Hive

  • Latency in Query Processing
    Queries in Hive often take longer to execute compared to traditional databases, as they are converted to MapReduce jobs which can introduce significant latency.
  • Limited Real-time Processing
    Hive is designed for batch processing and is not suitable for real-time analytics due to its reliance on MapReduce, which is not optimized for low-latency operations.
  • Complex Configuration
    Setting up Hive and configuring it to work optimally within a Hadoop cluster can be complex and require a significant amount of effort and expertise.
  • Lack of Support for Transactions
    Hive does not natively support full ACID transactions, which can be a limitation for applications that require consistent transaction management across large datasets.
  • Dependency on Hadoop
    Hive's reliance on the Hadoop ecosystem means it inherits some of Hadoop's limitations, such as a steep learning curve and the need for substantial resources to manage a cluster.

Azure IoT Hub videos

+ Add

Azure Friday | Azure IoT Hub

More videos:

  • Review - How Does Azure IoT Hub Work?

Apache Hive videos

+ Add

Hive vs Impala - Comparing Apache Hive vs Apache Impala

Category Popularity

0-100% (relative to Azure IoT Hub and Apache Hive)

Azure IoT Hub

Apache Hive

IoT Platform
100 100%
IoT Platform
0% 0
Databases
0 0%
Databases
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Hive should be more popular than Azure IoT Hub. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Azure IoT Hub mentions (3)

  • Looking for Microsoft Azure based alternative to Adafruit IO Feeds
    Sure MS has a product. It's more expensive and harder to use, though...Azure IOT hub - https://azure.microsoft.com/en-us/products/iot-hub. Source: almost 2 years ago
  • Getting Started With Azure IoT Hub
    Azure IoT Hub is a managed cloud service which provides bi-directional communication between the cloud and IoT devices. It is a platform as a service for building IoT solutions. Being an azure offering, it has security and scalability built-in as well as making it easy to integrate with other Azure services. - Source: dev.to / about 3 years ago
  • How to get the EK and Registration ID from a TPM 2.0 module on Raspian
    I am currently working on an IoT Project for my Bachelor's thesis. The goal is to gather data from an existing machine and send it to an Azure cloud via AMQP. To do this I have set up an IoT Hub and will be using the Azure IoT Edge runntime to connect and send the Data. For initial development, I have authenticated my devices to the cloud using symmetric keys generated by the IoT hub. Now I want to switch to... Source: over 3 years ago

Apache Hive mentions (8)

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What are some alternatives?

When comparing Azure IoT Hub and Apache Hive, you can also consider the following products

ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

AWS IoT - Easily and securely connect devices to the cloud.

Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.

Particle.io - Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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