Time and Location: Dec. 9thth, 2020, Wed., 10 a.m., Online seminar
 
Speaker #1: Ms. Ruonan Wu
Title: Database Comparison for Managing High Cardinality Time Series Data
Abstract: Time Series Databases (TSDBs) are specialized for storing and query time series data. With the growth of data centers in scale, the development of database is also growing to handle such amounts of data. There is a wide variety of database to choose from. Previously, InfluxDB is deployed and the application of Influx DB on monitoring Quanah Cluster is very successful. However, the current situation is that InfluxDB is not able to hold such many collected matrices with the new iDRAC9 model used in RedRaider Cluster. It is urgent to find an appropriate time series database solution that can deliver high performance, scalability, and reliability for a larger scale cluster. This project is looking for an optimized database for handling times series data such as, sensor data collected via iDRAC9 and job data via Slurm. It should support management of both real-time, streaming data and historical data with a single database architecture. This work also includes using new servers to compare different databases. Query across multiple databases on same server also need to be tested to obtain optimum solution.