Paper and Presentation: Comparison of Database Solutions for Hot and Cold paths of Azure IoT Data streamlines, e.g. Azure Cosmos, Data Lake, Lake Blob, Time Series Insights,...
This paper aims to compare various database solutions offered by Microsoft Azure for Hot and Cold paths of IoT Data streamlines. Specifically, the following solutions will be evaluated: Azure Cosmos, Data Lake, Lake Blob, and Time Series Insights.
The Hot path refers to the real-time data stream that requires immediate processing and analysis, while the Cold path refers to the data that is stored for long-term analytics and reporting. Both paths have their unique requirements and need to be handled differently.
This paper will evaluate the different database solutions based on the following criteria:
Data ingestion and processing capabilities
Scalability and performance
Cost-effectiveness
Integration with other Azure services
Data querying and analysis capabilities
Based on these criteria, we will provide a comprehensive comparison of the various database solutions and recommend the most suitable solution for different use cases. Table of Contents
Introduction
Hot Path Database Solutions
Azure Cosmos
Data Lake
Cold Path Database Solutions
Lake Blob
Time Series Insights
Comparison of Database Solutions
Recommendation
Conclusion
References