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ApacheKafka is an open-source , distributed streaming platform that allows developers to build real-time, event-driven applications. With ApacheKafka, developers can build applications that continuously use streaming data records and deliver real-time experiences to users. How does ApacheKafka work?
Be sure to check out his talk, “ ApacheKafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the ApacheKafka ecosystem.
Real-Time Data Ingestion Examples Here are some examples of real-time data ingestion applications: Internet of Things (IoT) Devices: IoT devices generate a vast amount of data, such as temperature, humidity, location, and sensor readings.
Internet of Things (IoT): Devices such as sensors, smart appliances, and wearables continuously collect and transmit data. Cloud Storage: Services like Amazon S3, Google Cloud Storage, and Microsoft Azure Blob Storage provide scalable storage solutions that can accommodate massive datasets with ease.
Internet of Things (IoT): Devices such as sensors, smart appliances, and wearables continuously collect and transmit data. Cloud Storage: Services like Amazon S3, Google Cloud Storage, and Microsoft Azure Blob Storage provide scalable storage solutions that can accommodate massive datasets with ease.
There are a number of tools that can help with streaming data collection and processing, some popular ones include: ApacheKafka : An open-source, distributed event streaming platform that can handle millions of events per second. Azure Stream Analytics : A cloud-based service that can be used to process streaming data in real-time.
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