What Time Series Data Means for You

Time series data management continues to underpin huge swaths of application deployments today across on premises, and increasingly, cloud native environments. Whether it’s video streaming, real-time financial security data management, energy utility management or any application that requires time stamps for often very complex datasets at massive scales, time series data will play an integral role. Today’s time series data platforms can typically be used for data analysis and forecasting by processing millions of data points per second. Pricing has also become affordable for a growing number of enterprises seeking high-powered data analysis as a way to distinguish themselves from the competition. These organizations also do not necessarily have the financial backing that the world’s largest financial institutions or Fortune 100 companies have at their disposal. In this The New Stack Makers podcast, Chris Churilo, responsible for technical product marketing at InfluxData, offer some background and perspective on why organizations increasingly rely on time series databases to “make products or services better.” Churilo also discussed why organizations are shifting their databases and management to cloud environments and why InfluxData recently extended to its InfluxDB Cloud 2.0 serverless time-series Platform as a Service (PaaS) to include Google Cloud Platform (GCP) as well as Amazon Web Services (AWS) cloud environments. “Time series data is useful for monitoring anything that you want to make improvements on,” Churilo said. “So, of course, your cloud infrastructure is one thing that you definitely want to always be monitoring to make sure that you can provide the best service, especially if you have applications sitting on top of it that are customer-facing or even internally-facing — no one can tolerate having a slow application.”