Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
Written for developers and architects, this guide will cover:
- Challenges involved with managing time series data
- Exploring different time series schema designs
- Impacts of schema design on memory and disk utilization
- How to query, analyze and present time series data using MongoDB visualization and data science tools
Download the guide to learn more about the best practices in managing time series data with MongoDB.
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