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Azure Stream Analytics VS AWS IoT Core

Compare Azure Stream Analytics VS AWS IoT Core and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Azure Stream Analytics logo Azure Stream Analytics

Azure Stream Analytics offers real-time stream processing in the cloud.

AWS IoT Core logo AWS IoT Core

Whether building a connected home application for home security or building an industrial application to proactively identify equipment breakdown, you can use AWS IoT Core to securely communicate with and gather data from your diverse fleet of IoT d…
  • Azure Stream Analytics Landing page
    Landing page //
    2023-01-21
  • AWS IoT Core Landing page
    Landing page //
    2022-02-05

Azure Stream Analytics features and specs

  • Real-time Data Processing
    Azure Stream Analytics allows for real-time data processing, which enables businesses to analyze and process data as it is generated to make faster decisions.
  • Ease of Use
    The platform provides a simple and intuitive interface for setting up streaming jobs, making it accessible even for users with limited technical expertise.
  • Scalability
    It is designed to handle large volumes of data, allowing for automatic scaling to accommodate more data without compromising performance.
  • Integration with Azure Ecosystem
    Seamless integration with other Azure services like Azure Functions, Azure Event Hubs, and Azure Blob Storage allows for a unified cloud ecosystem.
  • Cost Efficiency
    Its pricing model based on the volume of data processed makes it cost-efficient, especially for projects that require variable or burst data processing.
  • Support for Multiple Input Sources
    It supports multiple input sources such as IoT Hub, Event Hub, and Azure Blob Storage, providing flexibility in designing the data flow architecture.

Possible disadvantages of Azure Stream Analytics

  • Limited Machine Learning Capabilities
    Azure Stream Analytics has limited built-in capabilities for complex machine learning models, requiring integration with other services for advanced analytics.
  • Complex Queries
    While powerful, the query language can be complex for users unfamiliar with SQL, potentially necessitating a learning curve for new users.
  • Geographic Availability
    Not all features are available in every Azure region, which may limit its usability for some global operations depending on the region's support.
  • Debugging and Monitoring
    Some users have reported that debugging and monitoring issues can be challenging due to limited tools compared to other more mature data processing platforms.
  • Dependency on Internet Connectivity
    As a cloud-based service, it requires reliable internet connectivity, which can be a constraint for operations in environments with unstable connections.

AWS IoT Core features and specs

  • Scalability
    AWS IoT Core can automatically scale to accommodate billions of devices and trillions of messages, making it suitable for both small and large IoT deployments.
  • Integration with AWS Services
    Seamlessly integrates with other AWS services, such as AWS Lambda, Amazon S3, and Amazon DynamoDB, allowing for complex workflows and data processing.
  • Security
    Provides robust security features including mutual authentication, end-to-end encryption, and fine-grained access control to protect data.
  • Device Management
    Offers features for managing device fleets, such as registering devices, managing permissions, and monitoring connectivity status.
  • MQTT Support
    Supports the popular MQTT protocol, which is lightweight and ideal for connecting remote devices with minimal bandwidth.
  • Serverless Architecture
    Supports a serverless approach, which reduces the need for infrastructure management and allows developers to focus more on building applications.

Possible disadvantages of AWS IoT Core

  • Complex Pricing
    The pricing structure can be complex, involving costs for messaging, data transfer, and other AWS services, which can make it challenging to estimate costs accurately.
  • Steep Learning Curve
    The platform's extensive features and broad integration options can be overwhelming for new users or those unfamiliar with AWS services.
  • Vendor Lock-in
    Using AWS IoT Core can lead to potential vendor lock-in due to the deep integration with the broader suite of AWS services.
  • Latency
    Depending on the geographical location of devices and nearest AWS regions, there may be concerns about latency for time-sensitive applications.
  • Limited Offline Capabilities
    Primarily designed for cloud connectivity, so offline capabilities might require additional configuration or third-party solutions.

Azure Stream Analytics videos

+ Add

Azure Stream Analytics

More videos:

  • Review - Real-time Analytics with Azure Stream Analytics
  • Demo - Introduction to Azure Stream Analytics + Demo

AWS IoT Core videos

+ Add

Getting Started with AWS IoT Core for LoRaWAN

More videos:

  • Review - How can I start publishing messages to AWS IoT Core from my device?

Category Popularity

0-100% (relative to Azure Stream Analytics and AWS IoT Core)

Azure Stream Analytics

AWS IoT Core

Stream Processing
100 100%
Stream Processing
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Data Management
100 100%
Data Management
0% 0
Analytics
22 22%
Analytics
78% 78

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Azure Stream Analytics and AWS IoT Core

Azure Stream Analytics Reviews

We have no reviews of Azure Stream Analytics yet.
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AWS IoT Core Reviews

Open Source Internet of Things (IoT) Platforms
It is a managed cloud service. AWS IoT Core will allow devices to connect with the cloud and interact with the other devices and cloud applications. It provides support for HTTP, lightweight communication protocol, and MQTT.
Source: jansutris10.medium.com
14 of the Best IoT Platforms to Watch in 2021
AWS IoT Core is a behemoth in IoT platforms, and is the backbone of many fascinating projects such as Expedia, AirBnB, and CoinBase. With support for device software such as FreeRTOS and AWS IoT Greengrass, AWS IoT Core encompasses a vastly superior ecosystem of products allowing development in smart homes and industrial automation. All AWS data is visualized on an AWS IoT...
Source: www.iottechtrends.com

Social recommendations and mentions

Based on our record, AWS IoT Core seems to be more popular. It has been mentiond 9 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 Stream Analytics mentions (0)

We have not tracked any mentions of Azure Stream Analytics yet. Tracking of Azure Stream Analytics recommendations started around Mar 2021.

AWS IoT Core mentions (9)

  • AWS AppSync Events vs IoT Core
    AWS recently announced AppSync Events and it looks like very useful service. However when I was reading about it, it just felt like this is "just" a layer on top of IoT Core which exists for many years. Let's find out if this is the case... - Source: dev.to / 6 months ago
  • WebSockets, gRPC, MQTT, and SSE - Which Real-Time Notification Method Is For You?
    MQTT - AWS IoT Core offers a managed MQTT message broker, giving you easy access to your devices. Fun fact, this is what powers the notifications in Serverlesspresso. - Source: dev.to / over 1 year ago
  • Serverless Facial Recognition Voting Application Using AWS Services
    AWS IoT: For real-time communication between the server and the frontend application. - Source: dev.to / about 2 years ago
  • Building Serverlesspresso
    AWS IoT Core is a service that allows you to connect your devices securely to the AWS cloud and with ease. Option for device management, data processing as well as integration with other AWS services is provided. Click here for more on AWS IoT Core. - Source: dev.to / about 2 years ago
  • Use EventBridge to handle API requests
    From here you can do all sorts of actions. For example, the serverless-coffee project used IOT Core. With IOT Core you can notify the end-user with status updates. And notify the barista that what kind of coffee needs to be created. - Source: dev.to / about 2 years ago
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What are some alternatives?

When comparing Azure Stream Analytics and AWS IoT Core, you can also consider the following products

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

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

PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time

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

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Blynk.io - We make internet of things simple

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