Store time series data in an optimized columnar format, reducing storage and I/O demands for greater performance and scale.
Dramatically reduce your database storage footprint by more than 90% with columnar storage format and best-in-class compression algorithms.
Optimize your queries with compound secondary indexes on all fields to achieve faster queries at scale.
Support the entire time series data lifecycle from ingest, storage, analysis, and visualization to archiving.
Use window functions to calculate moving averages and sums over flexible time-based windows.
Handle missing data points using specialized gap filling and densification functions.
Ability to freely modify the data with updates and deletes giving you more flexibility and control.
Horizontally distribute large data sets to reduce latency and comply with data sovereignty regulations.
Learn how Digitread Connect converts industrial IoT data into leading-edge insight with MongoDB Time Series
Read the three-part blog on how to build a currency analysis platform with MongoDB
Perform analytics on your time series collections using the unified, expressive Query API to easily uncover insights and patterns.
Create graphs from times series collections and embed visualizations into your applications for a rich user experience.