Machine Learning and the Apache Kafka Ecosystem are a combination for training and deploying scalable analytical models, the deployment of an analytic model in a Kafka application for real-time predictions.

Elasticsearch allows you to search for transactions for user in real time across huge volumes of data, or use aggregations and visualisations to show the top ten selling products or trends in transactions over time.

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.

Amazon ML is a robust, cloud-based service that makes it easy for developers of all skill levels to use machine learning technology. Amazon ML provides visualization tools and wizards that guide you through the process of creating ML models without having to learn complex ML algorithms and technology

Azure Machine Learning can be used for any kind of machine learning, from classical ml to deep learning, supervised, and unsupervised learning. You can build, train, and track machine learning and deep-learning models in an Azure Machine Learning Workspace.