Gorilla: A Fast, Scalable, In-Memory Time Series Database

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Milvus: A Purpose-Built Vector Data Management System (2021, background): “, specialized graph engine [18], IoT engine [21], time series database [55], and scientific database [59].”
Accelerometer: Understanding Acceleration Opportunities for Data Center Overheads at Hyperscale (2020, methodology): “For each case study, we first measure the real production speedup using an internal tool called Operational Data Store (ODS) [19, 33, 96].”
MacroBase: Analytic Monitoring for the Internet of Things (2016, background): “ng hundreds of thousands of vehicles. 1. INTRODUCTION Data volumes are quickly outpacing human abilities to process them. Today, Twitter, LinkedIn, and Facebook each record over 12M events per second [10,63,79]. These volumes are growing and are becoming more common: machine-generated data sources s”
SoftSKU: Optimizing Server Architectures for Microservice Diversity @Scale (2019, methodology): “We collect most system-level performance data using an internal tool called Operational Data Store (ODS) [35–37].”
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction (2017, background): “Problems of similar nature arise in monitoring the health of data centers and predicting failures based on the longitudinal data of product and system usage statistics [6].”
MacroBase: Prioritizing Attention in Fast Data (2016, background): “Today, Twitter, LinkedIn, and Facebook each record over 12M events per second [10, 63, 79].”