Instead of having a static infrastructure that is unresponsive to your changing usage, Google’s cloud platform enables the infrastructure to dynamically scale along with your usage. This means you only pay for what you are using, when you are using it. We’ll create a simple proof of concept demonstrating this scaling behaviour when used with kdb+. This will utilize some …
Sequel to qsql
This post is a continuation of the earlier blog post titled “An Introduction to qsql”, found here, which would be helpful to read before continuing further into this topic. This part will deal with the use of delete and update. There will be a part on aggregations and it will end with a look at both by and fby. Let’s …
AquaQ Analytics NY Event [10.17.2019]
AquaQ is pleased to announce this years New York event will involve a kdb+ Architecture Workshop and an evening drinks reception: EVENT DATE : Thursday 17th October 2019 EVENT VENUE: W Hotel New York – Downtown Event Schedule : Architecture Workshop Start Time : 3.00PMThe workshop will cover all aspects of kdb+ market data capture system design, including: – the …
Tradefeedr, the Leading FX Data Analysis Platform Partners with Goldman Sachs, UBS & XTX Markets as the First Participants on its Platform
Great news on our joint venture Tradefeedr.com with Alexei Jiltsov and Balraj Bassi. Well done to the team for all the hard work. LONDON, Sept. 10, 2019 /PRNewswire/ — Founded in 2018 by Balraj Bassi and Alexei Jiltsov, Tradefeedr is a trusted independent intermediary which aggregates, analyses and disseminates trading information between capital market participants to aid data-driven decision making. The co-founders bring a …
An Introduction to qsql
This blog post gives users with a basic knowledge of SQL a brief introduction to querying q/kdb databases, with a focus on filtering data. If you are experimenting on an on-disk database, please read all the way to the bottom before starting as there are some important points about accessing partitioned data structures! q has its own syntax for querying …
Kafka with kdb+ and Java
Kafka is a distributed messaging service used to achieve a low-latency, high-throughput transfer of data using persistent logs to prevent loss of data. This blog will: Illustrate the various components used in Kafka. Show how Kafka can be used to share data between different technologies, for example, a Java producer and a kdb+ consumer. Highlight a use case for Kafka …
Grafana kdb+ Adaptor Update
One of the most requested features to our kdb+ Grafana adaptor was the ability to create panels from the results of server side functions. This most recent update to the adaptor continues to build on the SimpleJSON datasource created by Grafana by working around the limitation of the single drop down menu for queries, whilst also allowing parameters to be supplied. The adaptor is also integrated into TorQ …
TorQ Release v3.4
We are delighted to announce release v3.4 of TorQ, the latest instalment of our kdb+ framework; which can be found here. The main changes are outlined below. Grafana Adaptor Integration As part of this update we have included AquaQ’s recent release, the Grafana-KDB adaptor. With this inclusion, the adaptor script is loaded in to all TorQ processes, allowing connection via a Grafana session. Full installation & usage can be found in the original blog and TorQ documentation. …
Grafana – kdb+ adaptor
AquaQ Analytics are often involved in projects using different visualisation tools connected to kdb+. We have recently spent some time reviewing and then implementing a simple Grafana-kdb+ adaptor. This open-source script has been developed using the inbuilt Grafana SimpleJSON datasource and comes with the capability of table and time series visualisation and manipulation. Instructions for installation and usage can be …