Software Alternatives, Accelerators & Startups

ThingSpeak VS Apache Kafka

Compare ThingSpeak VS Apache Kafka and see what are their differences

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ThingSpeak logo ThingSpeak

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

Apache Kafka logo Apache Kafka

Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
  • ThingSpeak Landing page
    Landing page //
    2021-07-26
  • Apache Kafka Landing page
    Landing page //
    2022-10-01

ThingSpeak features and specs

  • Ease of Use
    ThingSpeak provides a user-friendly interface and extensive documentation, making it suitable for users with varying levels of technical expertise.
  • Real-time Data Processing
    It allows real-time data collection, analysis, and visualization, which can be beneficial for applications that require immediate feedback.
  • Integration with MATLAB
    Seamless integration with MATLAB allows users to leverage MATLAB's powerful data analysis and visualization tools for more advanced analysis.
  • API Support
    ThingSpeak provides RESTful APIs, making it easier to collect, store, and retrieve data from IoT devices and other sources.
  • Free Tier
    Offers a free tier for users to start with basic usage, which is useful for small projects or initial experimentation.
  • Community Support
    A broad community of users means more available resources such as tutorials, forums, and shared projects for learning and troubleshooting.

Possible disadvantages of ThingSpeak

  • Limited Free Tier
    The free version has limitations on the number of channels and data storage, which might not be sufficient for larger projects.
  • Dependence on Internet
    Requires a constant internet connection to transmit data to the cloud, which could be a drawback in remote or unstable network environments.
  • Data Privacy
    As a cloud-based service, data control and privacy can be concerns, especially for sensitive or proprietary information.
  • Limited Advanced Features
    Advanced data analytics features are relatively basic compared to more comprehensive IoT platforms, which might limit its use for more complex requirements.
  • Cost for Pro Features
    To access more advanced features and larger data capacities, a paid plan is required, which may not be cost-effective for all users.
  • Latency
    For applications requiring ultra-low latency, using a cloud service can introduce delays that might be unacceptable.

Apache Kafka features and specs

  • High Throughput
    Kafka is capable of handling thousands of messages per second due to its distributed architecture, making it suitable for applications that require high throughput.
  • Scalability
    Kafka can easily scale horizontally by adding more brokers to a cluster, making it highly scalable to serve increased loads.
  • Fault Tolerance
    Kafka has built-in replication, ensuring that data is replicated across multiple brokers, providing fault tolerance and high availability.
  • Durability
    Kafka ensures data durability by writing data to disk, which can be replicated to other nodes, ensuring data is not lost even if a broker fails.
  • Real-time Processing
    Kafka supports real-time data streaming, enabling applications to process and react to data as it arrives.
  • Decoupling of Systems
    Kafka acts as a buffer and decouples the production and consumption of messages, allowing independent scaling and management of producers and consumers.
  • Wide Ecosystem
    The Kafka ecosystem includes various tools and connectors such as Kafka Streams, Kafka Connect, and KSQL, which enrich the functionality of Kafka.
  • Strong Community Support
    Kafka has strong community support and extensive documentation, making it easier for developers to find help and resources.

Possible disadvantages of Apache Kafka

  • Complex Setup and Management
    Kafka's distributed nature can make initial setup and ongoing management complex, requiring expert knowledge and significant administrative effort.
  • Operational Overhead
    Running Kafka clusters involves additional operational overhead, including hardware provisioning, monitoring, tuning, and scaling.
  • Latency Sensitivity
    Despite its high throughput, Kafka may experience increased latency in certain scenarios, especially when configured for high durability and consistency.
  • Learning Curve
    The concepts and architecture of Kafka can be difficult for new users to grasp, leading to a steep learning curve.
  • Hardware Intensive
    Kafka's performance characteristics often require dedicated and powerful hardware, which can be costly to procure and maintain.
  • Dependency Management
    Managing Kafka's dependencies and ensuring compatibility between versions of Kafka, Zookeeper, and other ecosystem tools can be challenging.
  • Limited Support for Small Messages
    Kafka is optimized for large throughput and can be inefficient for applications that require handling a lot of small messages, where overhead can become significant.
  • Operational Complexity for Small Teams
    Smaller teams might find the operational complexity and maintenance burden of Kafka difficult to manage without a dedicated operations or DevOps team.

ThingSpeak videos

How to Analyze IoT Data in ThingSpeak

More videos:

  • Review - Review Higrow Board ESP32 and Aplication on Thingspeak #IoT #ESP32
  • Tutorial - How to Use ThingSpeak with Arduino

Apache Kafka videos

Apache Kafka Tutorial | What is Apache Kafka? | Kafka Tutorial for Beginners | Edureka

More videos:

  • Review - Apache Kafka - Getting Started - Kafka Multi-node Cluster - Review Properties
  • Review - 4. Apache Kafka Fundamentals | Confluent Fundamentals for Apache Kafka®
  • Review - Apache Kafka in 6 minutes
  • Review - Apache Kafka Explained (Comprehensive Overview)
  • Review - 2. Motivations and Customer Use Cases | Apache Kafka Fundamentals

Category Popularity

0-100% (relative to ThingSpeak and Apache Kafka)
Data Dashboard
100 100%
0% 0
Stream Processing
0 0%
100% 100
IoT Platform
100 100%
0% 0
Data Integration
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare ThingSpeak and Apache Kafka

ThingSpeak Reviews

Best IoT Platforms in 2022 for Small Business
ThingSpeak is an IoT platform that uses channels to store data sent from apps or devices. A special feature of ThingSpeak is that you can create your own channel to collect the analyzed data hence giving a great level of flexibility to the users. You can also collect the data from the public (for example, ThingSpeak channel 12397 – Weather Station) and configure to write...
Source: www.fogwing.io
Open Source Internet of Things (IoT) Platforms
Known as the cloud IoT platform with MATLAB analytics, ThingSpeak allows you to aggregate, analyze, and visualize live data streams. IoT devices send their live data directly to ThingSpeak. From there, you create instant visualizations and can send alerts using web services. Essentially, however, you write and execute MATLAB code to do your data preparation, visualization...
14 of the Best IoT Platforms to Watch in 2021
ThingSpeak is a 100% analytics platform which supports advanced developer applications in environmental monitoring, energy, and smart farming. All the analysis is done on Matlab, and you can utilize the data insights for really cool stuff. For example, connecting an IoT device to Twitter and sending alerts. The best part is that using data for a certain interval is free....

Apache Kafka Reviews

Best ETL Tools: A Curated List
Debezium is an open-source Change Data Capture (CDC) tool that originated from RedHat. It leverages Apache Kafka and Kafka Connect to enable real-time data replication from databases. Debezium was partly inspired by Martin Kleppmann’s "Turning the Database Inside Out" concept, which emphasized the power of the CDC for modern data pipelines.
Source: estuary.dev
Best message queue for cloud-native apps
If you take the time to sort out the history of message queues, you will find a very interesting phenomenon. Most of the currently popular message queues were born around 2010. For example, Apache Kafka was born at LinkedIn in 2010, Derek Collison developed Nats in 2010, and Apache Pulsar was born at Yahoo in 2012. What is the reason for this?
Source: docs.vanus.ai
Are Free, Open-Source Message Queues Right For You?
Apache Kafka is a highly scalable and robust messaging queue system designed by LinkedIn and donated to the Apache Software Foundation. It's ideal for real-time data streaming and processing, providing high throughput for publishing and subscribing to records or messages. Kafka is typically used in scenarios that require real-time analytics and monitoring, IoT applications,...
Source: blog.iron.io
10 Best Open Source ETL Tools for Data Integration
It is difficult to anticipate the exact demand for open-source tools in 2023 because it depends on various factors and emerging trends. However, open-source solutions such as Kubernetes for container orchestration, TensorFlow for machine learning, Apache Kafka for real-time data streaming, and Prometheus for monitoring and observability are expected to grow in prominence in...
Source: testsigma.com
11 Best FREE Open-Source ETL Tools in 2024
Apache Kafka is an Open-Source Data Streaming Tool written in Scala and Java. It publishes and subscribes to a stream of records in a fault-tolerant manner and provides a unified, high-throughput, and low-latency platform to manage data.
Source: hevodata.com

Social recommendations and mentions

Based on our record, Apache Kafka seems to be a lot more popular than ThingSpeak. While we know about 144 links to Apache Kafka, we've tracked only 9 mentions of ThingSpeak. 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.

ThingSpeak mentions (9)

  • Kotlin/ Thingspeak Interfacing.
    First of all, you need to ask yourself how familiar you are with MatLab. Then from a dev point of view, could you use an API to reference cloud data then apply analytics. Great intro to IoT. I can see that company going far in 5-10 and may invest based on trajectory. Https://thingspeak.com. Source: over 1 year ago
  • Google sheets and esp32
    You can use solutions like thingspeak https://thingspeak.com/. Source: about 2 years ago
  • Help me check my circuit for my self-sustaining water meter
    I'm not sure yet. Maybe something custom, but probably not. I was thinking about Thingspeak before. Source: about 2 years ago
  • Displaying readings to website?
    I haven't got around to MQTT yet, but as an easy interim solution I recommend ThingSpeak https://thingspeak.com/ as you can set up an account for free and getting an ESP to send data to it is trivial. Plus you can access it via the web, or embed their graphs and dials into a webpage. The graphics are a bit meh though. Source: over 2 years ago
  • i have an idea for a database+arduino+matlab, i need some help plz
    ThingSpeak for IoT Projects Data collection in the cloud with advanced data analysis using MATLAB Https://thingspeak.com/. Source: over 2 years ago
View more

Apache Kafka mentions (144)

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What are some alternatives?

When comparing ThingSpeak and Apache Kafka, you can also consider the following products

Blynk.io - We make internet of things simple

RabbitMQ - RabbitMQ is an open source message broker software.

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

StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.

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.

Histats - Start tracking your visitors in 1 minute!