Optimizing Compression for Time Series Data

ServiceNow Computer Science, 2018-19

Liaison(s): James Capaldo ’92, Magaly Drant, Vincent Seguin, Meg Sharkey
Advisor(s): Ran Libeskind-Hadas
Students(s): Maya Minier (PM-F), Dhruv Sawhney, Eleanor White (PM-S), Kate Woolverton

ServiceNow maintains enormous amounts of time series data on behalf of its customers and seeks a solution to achieve lossless compression in a real-time system. The solution will be evaluated on the basis of compression ratio and read/write speed. We will discuss our process of implementing and evaluating various compression algorithms and our findings regarding their performance.