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Particle.io VS Hadoop

Compare Particle.io VS Hadoop and see what are their differences

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Particle.io logo Particle.io

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

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Particle.io Landing page
    Landing page //
    2023-09-23
  • Hadoop Landing page
    Landing page //
    2021-09-17

Particle.io features and specs

  • Comprehensive IoT Ecosystem
    Particle.io offers a complete IoT ecosystem with hardware, software, and cloud integration, making it easier for developers to build, deploy, and manage IoT solutions.
  • Device Management
    It provides robust device management features, allowing users to monitor and control a large number of devices remotely, ensuring better scalability and maintenance.
  • Cloud Connectivity
    Particle’s devices come with built-in cloud connectivity, which saves time and effort in setting up secure and reliable communications for IoT devices.
  • Extensive Documentation
    Particle.io offers extensive and well-organized documentation, making it easier for both beginners and experienced developers to get started and troubleshoot issues.
  • Community Support
    Particle.io has a strong community of developers who contribute to forums and share knowledge, aiding in problem-solving and project development.
  • Security
    Particle prioritizes security, providing features like over-the-air updates, secure boot, and encrypted communications, ensuring that IoT deployments are secure.
  • Development Tools
    It offers powerful development tools, including a web IDE, local development environment, and mobile app, catering to different user preferences.

Possible disadvantages of Particle.io

  • Cost
    Particle’s comprehensive solution can be more expensive compared to other DIY or less integrated IoT solutions, potentially making it less appealing for hobbyists or budget-constrained projects.
  • Learning Curve
    Despite extensive documentation, the breadth of features and services may present a steeper learning curve for new users or those less familiar with IoT concepts.
  • Hardware Dependence
    Users may find themselves dependent on Particle’s specific hardware offerings, which could limit flexibility or increase costs if alternative hardware needs to be integrated.
  • Service Dependency
    Reliance on Particle’s cloud services implies that any service downtime or changes in service terms could impact one's IoT projects significantly.
  • Complexity
    For simple IoT applications, the extensive features of Particle.io might be overkill, adding unnecessary complexity to projects that do not require advanced capabilities.

Hadoop features and specs

  • Scalability
    Hadoop can easily scale from a single server to thousands of machines, each offering local computation and storage.
  • Cost-Effective
    It utilizes a distributed infrastructure, allowing you to use low-cost commodity hardware to store and process large datasets.
  • Fault Tolerance
    Hadoop automatically maintains multiple copies of all data and can automatically recover data on failure of nodes, ensuring high availability.
  • Flexibility
    It can process a wide variety of structured and unstructured data, including logs, images, audio, video, and more.
  • Parallel Processing
    Hadoop's MapReduce framework enables the parallel processing of large datasets across a distributed cluster.
  • Community Support
    As an Apache project, Hadoop has robust community support and a vast ecosystem of related tools and extensions.

Possible disadvantages of Hadoop

  • Complexity
    Setting up, maintaining, and tuning a Hadoop cluster can be complex and often requires specialized knowledge.
  • Overhead
    The MapReduce model can introduce additional overhead, particularly for tasks that require low-latency processing.
  • Security
    While improvements have been made, Hadoop's security model is considered less mature compared to some other data processing systems.
  • Hardware Requirements
    Though it can run on commodity hardware, Hadoop can still require significant computational and storage resources for larger datasets.
  • Lack of Real-Time Processing
    Hadoop is mainly designed for batch processing and is not well-suited for real-time data analytics, which can be a limitation for certain applications.
  • Data Integrity
    Distributed systems face challenges in maintaining data integrity and consistency, and Hadoop is no exception.

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!

Hadoop videos

+ Add

What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Category Popularity

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

Particle.io

Hadoop

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

Share your experience with using Particle.io and Hadoop. 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 Particle.io and Hadoop

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

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
Source: www.datacamp.com
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
Source: www.analytixlabs.co.in
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Hadoop should be more popular than Particle.io. It has been mentiond 25 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.

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 2 years 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 3 years ago
  • KnowYourCrypto #51: BitTorrent Token (BTT)
    I really dig your KYC reports. Please do Particl particle.io next :). Source: over 3 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 4 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 4 years ago
View more

Hadoop mentions (25)

  • Apache Hadoop: Open Source Business Model, Funding, and Community
    This post provides an in‐depth look at Apache Hadoop, a transformative distributed computing framework built on an open source business model. We explore its history, innovative open funding strategies, the influence of the Apache License 2.0, and the vibrant community that drives its continuous evolution. Additionally, we examine practical use cases, upcoming challenges in scaling big data processing, and future... - Source: dev.to / 7 days ago
  • What is Apache Kafka? The Open Source Business Model, Funding, and Community
    Modular Integration: Thanks to its modular approach, Kafka integrates seamlessly with other systems including container orchestration platforms like Kubernetes and third-party tools such as Apache Hadoop. - Source: dev.to / 7 days ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Over the years, Indian developers have played increasingly vital roles in many international projects. From contributions to frameworks such as Kubernetes and Apache Hadoop to the emergence of homegrown platforms like OpenStack India, India has steadily carved out a global reputation as a powerhouse of open source talent. - Source: dev.to / 14 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 2 months ago
  • Apache Hadoop: Pioneering Open Source Innovation in Big Data
    Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / 2 months ago
View more

What are some alternatives?

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

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

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

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.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

AWS Greengrass - Local compute, messaging, data caching, and synch capabilities for connected devices

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

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