Below you'll find a list of all posts that have been tagged as “data capture”
Here at AquaQ we have years of experience using kdb+ in the financial sector, helping our clients capture, analyse and derive value from their data. We always take a keen interest in technologies that will help us solve new problems, or provide better solutions for existing problems. To this end Apache Arrow is very interesting. Arrow describes itself as a …
For anyone who has used TorQ, you will most likely be familiar with the Finance Starter Pack. The starter pack is an example data capture system that is based on randomly generated equity data. It was created with the purpose of showing how to set up an example TorQ installation and how different applications can be built and deployed on …
We are pleased to announce that due to popular demand we’ve added new content to our online training course. The additional material is on supporting a kdb+ system (something we have some experience of). The new material covers: overview of a real time data capture architecture (kdb+tick) kdb+tick setup health checking, monitoring, support and maintenance of a data capture system on …
Many financial institutions use kdb+ tick to capture and store market data. The same technology stack can be used to capture, store and analyse other forms of real time streaming data including sensor data from manufacturing production lines, usage data from utility smart meters, or telemetry data from Formula 1 cars. At AquaQ we provide onsite and nearshore 24/7 support …
The aim of this article is give an understanding of how kdb+ uses and releases memory, and the options available to modify the behaviour. kdb+ allocates memory in powers of 2. A vector of data will always be placed into a memory block which is the next power of two up from the raw data size (and allowing for some …
