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Learning KX
What do you like best about the product?
It's very fast to run, and when you're familiar with the language, it's very easy to write programs.
What do you dislike about the product?
It has a very high entry barrier due to its complex syntax and being a functional language.
What problems is the product solving and how is that benefiting you?
It helps me with data analysis.
Kx - the finest database to rule them all
What do you like best about the product?
Willingness to partner with users and customers
Good support across multiple channels (email, forums, listbox)
Timely release of features to address emerging developments (eg., vector db)
Good support across multiple channels (email, forums, listbox)
Timely release of features to address emerging developments (eg., vector db)
What do you dislike about the product?
Tutorials require understanding of KDB+ to resolve issues. A better managed learning management system will greatly help in adoption.
Needs to foster a more collaborative approach - eg., open sourcing pyKx was a great step. Other features such as REST API should be ideally released to the public so that access to basic functionalities are made more widely accessible
Needs to foster a more collaborative approach - eg., open sourcing pyKx was a great step. Other features such as REST API should be ideally released to the public so that access to basic functionalities are made more widely accessible
What problems is the product solving and how is that benefiting you?
Kx supports all major enterprise needs for high-performance computing especially with large TB-PB scale databases that would otherwise take 10x the number of resources and 10x the cost.
KDB is second-to-none for wrangling time series data
What do you like best about the product?
Fast, efficient, highly expressive terse syntax that is beautifully designed and well considered. The ability to mix programming and database primitives together can lead to some very elegant solutions. KDB Developer is a nice addition for EDA/charting. Performance is as fast as the metal allows, and use of multicore is transparent and easy.
What do you dislike about the product?
Steep learning curve; it probably takes some months to really get productive.
What problems is the product solving and how is that benefiting you?
Wrangling time series data for ML pipelines, EDA work, feature engineering.
KX technology delivers unmatched speed in data analytics
What do you like best about the product?
KX real-time data processing capabilities have been updaralleled, enabling us to make swift, data-driven decision in the dynamic capital markets landscape.
KX is the de-facto technology for real-time analtyics.
KX is the de-facto technology for real-time analtyics.
What do you dislike about the product?
While KX offers powerful real-time analytics, its steep learning curve and specialized adoption, slowed its cloud progress compared to other open-source mainstream technologies.
What problems is the product solving and how is that benefiting you?
KX has enabled various research and analytics initiatives that lead to net business value.
Concise, efficient & powerful
What do you like best about the product?
The q language - an incredibly efficient way to write code. Once the initial learning curve had been mastered, proficient q developers can achieve more with less, improving time-to-market, enabling market data and analytics systems to quickly innovate and keep up with changing market behaviour.
What do you dislike about the product?
When I first started writing kdb/q code in 2003, there was almost zero documentation to be found, but this has improved so much in 20 years - code.kx.com is an amazing resource and Kx Academy is a great tool to introduce new developers to the language.
What problems is the product solving and how is that benefiting you?
Kx technologies enables the customisation of real time and historical analytics offering insights into the trading process. The language is efficient to write and run, allowing detailed analytics to run over large-scale datasets really quickly, enabling users to pivot their perspectives and really dig deep into the data, improve understanding of market microstructure, uncover trading patterns and identify optimisation opportunities.
A beautiful and powerful query language and database for structured data
What do you like best about the product?
Insane performance and elegant minimalist syntax. Ajing billions of rows in a few seconds is perfect for time series data analysis.
What do you dislike about the product?
Steep learning curve. Threat of writing overly terse and confusing"write only" code ever present.
What problems is the product solving and how is that benefiting you?
1. Constructing central limit order book(s) and market data from order flow.
2. Joining market data to client executions to calculate transaction cost analysis for a variety of algorithmic strategies.
3. Deriving easy to use static data tables for instruments and customers.
2. Joining market data to client executions to calculate transaction cost analysis for a variety of algorithmic strategies.
3. Deriving easy to use static data tables for instruments and customers.
Unlimited power
What do you like best about the product?
Q/Kdb+ is extremely fast in large databases processing. Its code is fast and clean and it is integrated into Python via PyKX.
What do you dislike about the product?
The setup can be a bit triky, but once yo have it installed there are not problems.
What problems is the product solving and how is that benefiting you?
Extremely speeds up database processing compared to its competitors without having to leave the Python environent.
Speed, Scalable & Succinct
What do you like best about the product?
The terseness of Q language has won me. So much could be done in so less is amazing about KDB/q.
Even the whole application is only few KBs and that contains whole world of analytical functions with well thought implementation to work on huge dataset in a jiffy.
It's highly recommended for the scalable timeseries data specially for huge volumes where lot of analysis is involved and speed is the key.
Even the whole application is only few KBs and that contains whole world of analytical functions with well thought implementation to work on huge dataset in a jiffy.
It's highly recommended for the scalable timeseries data specially for huge volumes where lot of analysis is involved and speed is the key.
What do you dislike about the product?
Though I have seen the documentation and online helps improving over last one decade, as compared to other traditional databases and languages, there is still a significant gap. Moreover, for many years, it has been a closed community with not much documents in public domain. But now, it's no more the same. There are a lot of forums and helps available.
What problems is the product solving and how is that benefiting you?
Storing the trading data and providing analytics on the data. I have used it as a KDB developer in several investment banks. It certainly gave results real quick in comparison to all other databases for the same amount of data.
KX kdb is one software for computation storage and middleware one ever need in financial industry
What do you like best about the product?
Based on strong fundamentals of computer engineering needed for next generation applications
What do you dislike about the product?
Slow learning if your are coming from non functional language background
What problems is the product solving and how is that benefiting you?
Forex analytics
After 20 years of use I still think "wow, that was fast"
What do you like best about the product?
KDB core is extremely capable of capturing and processing large volumes of timeseries data. Even after 20 years, it still produces moments of "wow, that was fast". The documentation has improved dramatically, barrier to entry reduced and the community of developers/number of partners has grown as a result. With the appropriate skills and experience, the q language and KDB are hard to beat for elegant and efficient timeseries analysis.
What do you dislike about the product?
The open frameworks and ancillary services solve a lot of the common problems and improved APIs increase access to the underlying data, but the core product is still quite raw and protection from bad user queries is still limited.
What problems is the product solving and how is that benefiting you?
Capture and analysis of timeseries data to support and optimise systematic trading systems.
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