Based on our record, Apache Flink should be more popular than ThingSpeak. It has been mentiond 29 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.
I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 4 days ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 19 days ago
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 2 months ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
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: 9 months ago
You can use solutions like thingspeak https://thingspeak.com/. Source: about 1 year ago
I'm not sure yet. Maybe something custom, but probably not. I was thinking about Thingspeak before. Source: about 1 year ago
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 1 year ago
ThingSpeak for IoT Projects Data collection in the cloud with advanced data analysis using MATLAB Https://thingspeak.com/. Source: over 1 year ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
AWS IoT - Easily and securely connect devices to the cloud.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
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.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
Blynk.io - We make internet of things simple