Reaching your performance, durability and efficiency goals in a production setup can be a challenge: there are about a million ways to deploy complex systems, and QuasarDB is no exception. In this series of blog posts, we will be taking you through the various aspects on how to implement a successful QuasarDB deployment in production.
Our use case In a nutshell, Quasar helps you anticipate the unpredicted.
Industrial Internet of Things (IIoT) is facing the new challenge of having to ingest very high volume of timeseries data and perform complex analysis in real time. In this blog post, we share with you the lessons we’ve learned along the way.
QuasarDB is the fastest timeseries database in the world by ingestion speed (and probably by querying speed, but it’s very hard to establish objectively), by a significant margin. In the 3.9 branch, we furthered our advance further, and we are working to deliver another major performance boost in the following releases.
Although QuasarDB is mostly run on Linux, most of the development team works primarily on Windows using Visual Studio. It’s because VS has the most advanced native debugger, sitting on top of the Windows Debug API.
