TimeStored Blog

kdb – 2017 in Review

Notable events this year or possibly the previous year due to incoherent memory issues:

• KX went open on APIs – Improved and open sourced python, R, java and kafka interfaces.
  • Java Driver – Got some new serialization functionality
  • PyQ – KX acquired the rights
  • The fusion/interface/machine-learning team at kdb promise to keep bringing improvements
• KX went to the cloud – There is now a cloud offering of kdb that is dynamically costed based on usage. It’s for existing customers only so far. Beta is available for personal use but kx may terminate access at any time. You can’t run it on third party “clouds”, no AWS I guess.and costs $0.10 per core <=4 cores, $0.05 per core >4 cores.
• Other users outside finance start to use kdb – It’s great to see and this probably flows from First Derivatives (FD) having purchased KX. However a number of them seem like proof of concepts pushed by FD to demonstrate it can be used. Hopefully in 2018 we will see more independently operating users.
  • European Space Agency (ESA) – Al Worden an actual astronaut came to the London meetup with some great stories.
  • Partnerships with redbull racing and marketing companies demonstrate possible growth opportunities
• Technical:
  • Debugger with Stack Trace – You can now change the number of threads after startup
  • uj/ij changes – A change in the behaviour of ij/lj joins means we now have ljf/ujf functions to provide historical equivalents. This is an old change but worth mentioning here as more people are only now upgrading from kdb 2.x
  • Analyst – a jupyter notebook / tableau for kdb – KX launched an “analyst” product “a complete real time data transformation, exploration and discovery workflow. Using an intuitive point and click interface, the typical analyst can import, transform, filter, and visualize massive datasets without programming”