Mem0
Mem
Pieces for Developers
cognee
MemoryPlugin
Claude Memory
Mengram
Memory and continual learning for agents

AWS IoT
Countly
Particle.io
Axonize
Azure IoT Hub
AWS IoT Core
Ubidots
Open source data platform for the Internet of Things. ThingSpeak Features

Which is more popular?
Based on our record, ThingSpeak should be more popular than Supermemory. It has been mentioned 9 times since March 2021.
Website, pricing, platforms and company facts side by side.
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Supermemory
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| Website | supermemory.ai | thingspeak.com |
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In their own words, as submitted to SaaSHub.

Agents need memory. supermemory is building the default engine for memory and continual learning for agents, available through an API, plugins, and MCP. Memory that keeps learning. supermemory extracts and dreams on the context of every user, task, and tenant, stores it in a vector-graph...
No description of ThingSpeak yet.
What each product offers, as listed by its team.

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Possible disadvantages
An editorial look at what each product does well and who it suits.

Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
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Walkthroughs and reviews on video.
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How to Analyze IoT Data in ThingSpeak
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How often each product is chosen within a category, 0–100% relative to the other.

Share your experience with using Supermemory and ThingSpeak. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.

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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...
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...
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...
Recommendations tracked on public social media and blogs since March 2021.

This is usually a challenge that any developer has to take care of when building an AI agent. In fact, managing the context is one of the hardest problems when working with AI agents and there are many companies like SuperMemory, Mem0... - Source: dev.to / 4 months ago
Memory. I use Supermemory for this. Before, Pipa loaded context files and knew to update them. A memory tool adds teammate-like recall: goals, preferences, latest business state, and small details that should carry across runs. Good... - Source: dev.to / 5 months ago
We wire everything up with Vision Agents as the voice agent framework, Stream for WebRTC audio and video, OpenAI Realtime for speech in and speech out, Anam so the agent shows up as a face on the video, and Supermemory so answers come... - Source: dev.to / 6 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... Source: about 3 years ago
You can use solutions like thingspeak https://thingspeak.com/. Source: over 3 years ago
I'm not sure yet. Maybe something custom, but probably not. I was thinking about Thingspeak before. Source: over 3 years ago
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