Timeseries data = ingestion challenges 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!
This post is part of a series about the challenges behind database performance and how to accurately assess it. Why compression matters so much for timeseries data 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!
This post is part of a series about the challenges behind database performance and how to accurately assess it. You don’t care about performance 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 […]
This post is part of a series about the challenges behind database performance and how to accurately assess it. Purpose of an ingress benchmark 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 […]
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. The Penrose stairs of performance If you are following database innovation you can see that nearly every database vendor out […]
The security debacle. As a database user or administrator, you may have learnt that MongoDB recently took a very serious hit. A hit of over 28,000 hacked installs.
