comms_champion
ReductStore
comms_champion | ReductStore | |
---|---|---|
4 | 55 | |
245 | 186 | |
0.8% | 3.2% | |
0.0 | 9.6 | |
almost 3 years ago | 1 day ago | |
CMake | Rust | |
Mozilla Public License 2.0 | BUSL-1.1 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
comms_champion
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C++ Show and Tell - June 2023
I've been developing CommsChampion Ecosystem for about 9 years as my pet project. It's about easy and compile-time configurable implementation of binary communication protocols using C++11 programming language, with main focus on embedded systems (including bare-metal ones).
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What network messaging library do you recommend?
If this is the case, for the third stage of the application specific protocol handling I recommend CommsChampion Ecosystem.
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When to use template meta programming ?
I suppose if you develop something that is going to be used in a single project / product without much of a customization, then meta-programming is not really justified. The meta-programming is justified in many cases when you implement some kind of a library, which can be used in multiple independent products, and these uses may require some product specific customizations. For example, I'm developing a solution for implementing binary communication protocols for embedded systems in C++, called CommsChampion Ecosystem. The core component of which is the COMMS library. Every single use of this library requires different customization. Every application may require different polymorphic interface to handle its message objects. I use template meta-programming there to define virtual functions only needed by the application and not adding unnecessary ones. I also use template meta programming to allow customization of the storage data structures and may use different, more optimized code for some.
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Protocols that use a map/config to coordinate embedded device and host?
I use commschamp. You describe the protocol in an XML format, it only supports C++ though
ReductStore
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Keeping MQTT Data History with Node.js
The MQTT protocol is widely used in IoT applications because of its simplicity and ability to connect different data sources to applications using a publish/subscribe model. While many MQTT brokers support persistent sessions and can store message history while an MQTT client is unavailable, there may be cases where data needs to be stored for a longer period of time. In such cases it is recommended to use a time series database. There are many options available, but if you need to store unstructured data such as images, sensor data or Protobuf messages, you should consider using ReductStore as a MQTT database. It is a time series database specifically designed to store large amounts of unstructured data, optimised for IoT and edge computing.
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Computer Vision Made Simple with ReductStore and Roboflow
Computer vision is transforming industries by automating decision making based on visual data. From facial recognition to autonomous driving, the need for efficient computer vision solutions is growing rapidly. This article explores how Roboflow combined with ReductStore, a time-series object store optimized for managing continuous data streams, can improve computer vision applications. ReductStore is designed to efficiently handle high-frequency time-series data, such as video streams, making it a perfect fit for storing and retrieving large datasets generated by computer vision tasks.
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3 Ways to Store Computer Vision Data
ReductStore is a time series database for keeping a history of unstructured data. It is designed to solve the problem of data reduction and availability for AI/ML applications, where we have data of various sizes and formats continuously coming from data sources.
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How to Store Vibration Sensor Data | ReductStore vs InfluxDB
In this post, we compare ReductStore and InfluxDB in a real-world benchmark scenario, focusing on their write and read performance for high-frequency sensor data. We show how ReductStore's binary storage provides superior efficiency and scalability over InfluxDB when handling large volumes of unstructured time-series data.
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ReductStore v1.11.0: Changing labels and storage engine optimization
We are pleased to announce the release of the latest minor version of ReductStore, 1.11.0. ReductStore is a time series database designed for storing and managing large amounts of blob data.
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How to Keep a History of MQTT Data With Rust
ReductStore has client SDKs (software development kits) for many programming languages. This means you can easily use it in your existing system. For this example, we'll use the Rust SDK from ReductStore.
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Deploy ReductStore as Azure Virtual Machine
ReductStore, a time series database for unstructured data, is available as a virtual machine on the Azure Marketplace, providing Azure customers with an easy way to deploy out-of-the-box ReductStore instances on Azure VMs.
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How to Store Vibration Sensor Data | Part 1
Time series object stores such as ReductStore offer significant advantages over traditional TSDBs by efficiently managing vibration data in chunks. Volume-based retention policies and automated data replication ensure critical information is retained while minimizing storage constraints at the edge. By pre-processing and prioritizing metadata for replication, critical diagnostic data remains accessible even if raw data is overwritten.
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Getting Started with ReductStore in Python
This quick start guide will walk you through the process of installing and using the ReductStore Python Client SDK to read and write data to a ReductStore instance.
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How to Choose the Right MQTT Database
Since joining ReductStore's project, I've been exploring alternative solutions to get a better understanding about how the project fits into current echosystem.
What are some alternatives?
Jsonifier - A few classes for extremely fast json parsing/serializing in modern C++. Possibly the fastest json parser in C++. Possibly the fastest json serializer in C++.
thread-pool - A modern, fast, lightweight thread pool library based on C++20
seq - The seq library is a collection of original C++14 STL-like containers and related tools
reduct-cpp - ReductStore Client SDK for C++
system-bus-radio - Transmits AM radio on computers without radio transmitting hardware.
HMake - C++ build system that uses C++ for build configuration.
luos_engine - Open-source and real-time orchestrator for cyber-physical-systems, to easily design, test and deploy embedded applications and digital twins.
stick_man
key-manager - A desktop app for password management and creation, developed using Qt.
async-rusqlite - A tiny, executor agnostic library for using rusqlite in async contexts
p-net - PROFINET device stack for embedded devices
mk_parse_int - String to int (in C89).