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Streaming Real-Time Chat Messages Into Scylla With Apache Pulsar

At Scylla Summit 2022, I presented "FLiP Into Apache Pulsar Apps with ScyllaDB". Using the same content, in this blog, we'll demonstrate step-by-step how to build real-time messaging and streaming applications using a variety of OSS libraries, schemas, languages, frameworks, and tools utilizing ScyllaDB. We'll also introduce options from MQTT, Web Sockets, Java, Golang, Python, NodeJS, Apache NiFi, Kafka on Pulsar, Pulsar protocol, and more. You will learn how to quickly deploy an app to a production cloud cluster with StreamNative, and build your own fast applications using the Apache Pulsar and Scylla integration.

Before we jump into the how, let's review why this integration can be used for a speedy application build. Scylla is an ultra-fast, low-latency, high-throughput, open-source NoSQL platform that is fully compatible with Cassandra. Populating Scylla tables utilizing the Scylla-compatible Pulsar IO sink doesn't require any complex or specialized coding, and the sink makes it easy to load data to Scylla using a simple configuration file pointing to Pulsar topics that stream all events directly to Scylla tables.

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Unboxing the Most Amazing Edge AI Device Part 1 of 3 – NVIDIA Jetson Xavier NX

Fast, Intuitive, Powerful and Easy. 

This is the first of a series on articles on using the Jetson Xavier NX Developer kit for EdgeAI applications. This will include running various TensorFlow, Pytorch, MXNet and other frameworks. I will also show how to use this amazing device with Apache projects including the FLaNK Stack of Apache Flink, Apache Kafka, Apache NiFi, Apache MXNet and Apache NiFi - MiNiFi.

These are not words that one would usually use to define AI, Deep Learning, IoT or Edge Devices. They are now. There is a new tool for making what was incredibly slow and difficult to something that you can easily get your hands on and develop with. Supporting running multiple models simultaneously in containers with fast frame rates is not something I thought you could affordably run in robots and IoT devices. Now it is and this will drive some amazingly smart robots, drones, self-driving machines and applications that are not yet in prototypes.