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Amazon EMR VS Particle.io

Compare Amazon EMR VS Particle.io and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Particle.io logo Particle.io

Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.
  • Amazon EMR Landing page
    Landing page //
    2023-04-02
  • Particle.io Landing page
    Landing page //
    2023-09-23

Amazon EMR videos

+ Add

Amazon EMR Masterclass

More videos:

  • Review - Deep Dive into What’s New in Amazon EMR - AWS Online Tech Talks
  • Tutorial - How to use Apache Hive and DynamoDB using Amazon EMR

Particle.io videos

+ Add

Particle All In One Face Cream For Men Review | thatsNathan

More videos:

  • Review - MEN'S SKIN CARE ROUTINE ! ( PARTICLE CREAM REVIEW )
  • Tutorial - THE BEST MEN'S SKIN CARE ROUTINE! ( PARTICLE FOR MEN FACE WASH REVIEW ) How To Have Great Skin!

Category Popularity

0-100% (relative to Amazon EMR and Particle.io)

Amazon EMR

Particle.io

Data Dashboard
77 77%
Data Dashboard
23% 23
IoT Platform
0 0%
IoT Platform
100% 100
Big Data
100 100%
Big Data
0% 0
Data Warehousing
100 100%
Data Warehousing
0% 0

User comments

Share your experience with using Amazon EMR and Particle.io. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Amazon EMR and Particle.io

Amazon EMR Reviews

We have no reviews of Amazon EMR yet.
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Particle.io Reviews

Best IoT Platforms in 2022 for Small Business
The IoT solutions offered by Particle are fully integrated and it is an easy to use IoT platform with built-in infrastructure. The particle’s operating system and the Device OS are the differentiators as it expedites the complex integration between firmware, hardware, and network connectivity on all Particle devices.
Source: www.fogwing.io
Open Source Internet of Things (IoT) Platforms
Self-describing as a “complete edge-to-cloud platform”, Particle.io also contains all the building blocks for developing an IoT product. This includes connectivity, device management, and even the hardware required to prototype IoT solutions and scale quickly thanks to the robust infrastructure. The platform supports IoT data collection and over-the-air development in a...
Source: jansutris10.medium.com

Social recommendations and mentions

Amazon EMR might be a bit more popular than Particle.io. We know about 10 links to it since March 2021 and only 9 links to Particle.io. 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.

Amazon EMR mentions (10)

  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 1 year ago
  • What compute service i should use? Advice for a duck-tape kind of guy
    I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
  • Processing a large text file containing millions of records.
    This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
  • How to use Spark and Pandas to prepare big data
    Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 2 years ago
View more

Particle.io mentions (9)

  • What hardware do I need for a robot to upload information to the cloud?
    Look into AWS Greengrass, Robomaker, etc. If you're looking for more customization. Or you could use an all-in-one product like from particle.io if you'd more of an out-of-the-box solution. Source: about 1 year ago
  • Web developer becoming embedded engineer?
    5) look at using a GPRS or LTE (look at particle.io) cell monitor a fridge or freezer. Source: over 2 years ago
  • KnowYourCrypto #51: BitTorrent Token (BTT)
    I really dig your KYC reports. Please do Particl particle.io next :). Source: over 2 years ago
  • Cloud solution for ESP8266
    That's not how I read the OP's proposal. It sounds more like they want to build something like the service that http://particle.io/ appears to provide. Source: almost 3 years ago
  • Ray Ozzie's latest venture is a cheap IoT board with flat rate connectivity
    Looks cool! How does this differ from http://particle.io ? - Source: Hacker News / almost 3 years ago
View more

What are some alternatives?

When comparing Amazon EMR and Particle.io, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

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.

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