If there’s one thing that’s hard when managing timeseries data is just the sheer amount of it. Timeseries data has volume built-in because it’s cumulative. You don’t want a single picture: you want the whole movie!
Read MoreTags: quasardb, time series, performance
This post is part of a series about the challenges behind database performance and how to accurately assess it.
Whatever database engine you are using, efficient disk storage is always welcomed. When your 10 GiB become 100 GiB once in the database, that’s never a nice thing!
Read MoreTags: quasardb, time series, performance, compression, managed
This post is part of a series about the challenges behind database performance and how to accurately assess it.
When we started selling QuasarDB, we focused on its performance advantages and touted how great they were. The logic behind that was obvious: we were very strong in this area; thus we should bring the battle to where we are strong!
Read MoreTags: quasardb, software, time series, performance
This post is part of a series about the challenges behind database performance and how to accurately assess it.
When evaluating a timeseries database management system (later referred as TSDBMS or TSDB), one important dimension is the ingress speed (a.k.a. insertion or ingestion), that is, how fast the database can store new data points.
Read MoreTags: quasardb, time series, performance
This port is the first in a series about the challenges behind database performance and how to accurately assess it. In future posts, we will dig more into the specifics of benchmarks and design choices.
If you are following database innovation you can see that nearly every database vendor out there has at least one benchmark putting them in the first place. With every vendor selling the fastest database there is, you end up in a Penrose stairs situation where everyone is faster than everyone.
Read MoreTags: memory, optimization, process, software, performance