ThingSpeak Description
ThingSpeak™ is a cloud-based analytics platform designed for the Internet of Things (IoT) that enables users to collect, visualize, and analyze real-time data streams. It offers immediate graphical representations of the information submitted by connected devices, making it easier to interpret data. Additionally, the platform allows users to run MATLAB® code, facilitating real-time analysis and processing of incoming data. Often utilized for developing prototypes and proof of concept IoT applications that necessitate analytical capabilities, ThingSpeak exemplifies the growing trend of interconnected devices. This trend, known as the Internet of Things (IoT), involves a multitude of embedded devices that connect to the Internet, enabling communication between devices and humans alike. These devices frequently send sensor data to cloud storage and computing systems, where it is analyzed to extract valuable insights, thanks to the affordability of cloud computing and the surge in device connectivity. As these technologies advance, the potential applications for IoT continue to expand, paving the way for innovative solutions across various industries.
ThingSpeak Alternatives
RaimaDB
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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Qloo
Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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InfiConnector
An intermediateware that is installed on a variety of gateways. It connects equipment to InfiIoT, popular Internet of Things (IoT), or Industrial Internet of Things. It secures connections to various devices (e.g. PV panels, battery storage, HVACs and compressors) via industrial protocols (Modbus and OPC UA as well as cellular networks (5G and 5G). InfiConnector can be configured from cloud services to collect data and prepare data for data analysis or Artificial Intelligence (AI), cloud applications.
InfiConnector is a code-less edge computing interface and rule engine interface. It configures any machine to computer, diagnostic, alerting and log management services within a matter of minutes.
The light middleware needs 512MB RAM, 1 core CPU and 16GB disk. It is compatible with Ubuntu 20.04 or higher.
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AWS IoT Analytics
The data generated by IoT devices is predominantly unstructured, posing challenges for analysis using conventional analytics and business intelligence tools that cater to structured data formats. This type of data is often derived from devices that capture inherently noisy processes like temperature, motion, or sound, leading to frequent occurrences of significant gaps, corrupted messages, and erroneous readings that necessitate cleansing prior to any analytical work. Moreover, the significance of IoT data frequently relies on supplementary inputs from third-party data sources. For instance, vineyard irrigation systems enhance moisture sensor readings with rainfall data, assisting farmers in making informed decisions on when to irrigate their crops, thereby optimizing water usage and boosting harvest yields. AWS IoT Analytics simplifies and automates the complex steps involved in analyzing data from IoT devices, making it easier for users to gain insights. This service is fully managed and operates on a pay-as-you-go model, ensuring automatic scaling to accommodate varying data volumes. Consequently, organizations can leverage AWS IoT Analytics to advance their operational efficiencies and make data-driven decisions with greater ease.
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Integrations
Company Details
Company:
ThingSpeak
Headquarters:
United States
Website:
thingspeak.com
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support
ThingSpeak Features and Options
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