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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.
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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.
Excellent TSD for real time analytics and machine learning flows.
What do you like best about the product?
Extremely fast and reliable vector database!!
What do you dislike about the product?
It is still getting cloud ready with AWS, GCP and Azure. Most of use cases are in cloud now a days.
What problems is the product solving and how is that benefiting you?
Critical problems in Telecom and Automotive domains
The only real-time DB solution
What do you like best about the product?
Kdb+ is an excellent database management system that provides high performance and scalability. Essential for our real-time processing requirements and data management.
What do you dislike about the product?
Fairly niche technolgy, therfore a smaller q developer resource pool.
What problems is the product solving and how is that benefiting you?
Back testing, analysis and reporting.
User, partner and enthusiast
What do you like best about the product?
Completeness of the solution. Streaming analytics, data and analytics in memory and analysis of historical data on disk in a single solution is unique. KX can do everything another time series database can do but faster and more efficienctly - it also has unique temporal analytics capabilities others have never been able to replicate.
What do you dislike about the product?
The amount of times the user community has solved the same problems in marginally different ways. A managed cloud service on aws, open sourcing pykx and standardising kdb architect through kdb Insights are great steps forward to address this and allow builders to focus on outcomes rather than plumbing.
What problems is the product solving and how is that benefiting you?
Analysis of fast moving data with the benefit of historical context allowing faster decision making and greater insight for business processes.
Trading Analysis and Prototyping
What do you like best about the product?
Ease of use.
Analysis is simple, fast and easy to share.
Analysis is simple, fast and easy to share.
What do you dislike about the product?
Some simple features not available especially related to IPC
What problems is the product solving and how is that benefiting you?
Post and pre trade analysis
Elegant, reliable and super fast
What do you like best about the product?
KX makes light work of intricate time series transformations on vast amounts of data.
What do you dislike about the product?
This is an area currently at the forefront of focus for KX, with the recent release of PyKx.
But making an easy interface to the rich ocean of data vizualization / ML libraries etc in Python is something I've been excited about for a while.
But making an easy interface to the rich ocean of data vizualization / ML libraries etc in Python is something I've been excited about for a while.
What problems is the product solving and how is that benefiting you?
I work with the biggest dataset on the street, namely the US Equity Options market data feeds, both via OPRA and direct exchange feeds.
There is no other way that my team could perform our data ingestion, derived analytics and overnight calibration in sufficient time if we did not have KX.
There is no other way that my team could perform our data ingestion, derived analytics and overnight calibration in sufficient time if we did not have KX.
Kx in the cloud is unstoppable
What do you like best about the product?
Kx is the most performant analytical platform for timeseries and vector analytics. The AWS native integrations take Kx to the next level, and is already transforming how financial services organizations identify alpha in real-time, thanks to unlimited calculation performance in the cloud. The new AWS FinSpace managed Kdb will be a game changer as it takes the hassle out of running kdb and lets banks go straight to utilizing its power.
What do you dislike about the product?
None, now that it is managed in the cloud.
What problems is the product solving and how is that benefiting you?
Equity and FX alpha
Have been a business sponsor of KX for over 20 years using to support many businesses
What do you like best about the product?
Fundamentally KX core value was always about speed and efficiency. In the early days they didnt have many user tooling so you needed to find experts that were few and far between but at the end of the day the performance was differentiating and still is. Their focus on speed and minimising space for data is still their edge. They have evolved their tooling to make adoption easier but their underlying power is still their strength.
What do you dislike about the product?
It really depends on your perspective. It takes more effort than simpler languages to get things up and running. but if your target is scalable and you want a strong foundation like anything you have to put the effort in. From my perspective there are no dislikes other than the community is still perhaps too small
What problems is the product solving and how is that benefiting you?
processing massive amounts of real-time data, processing and deriving real time insights.
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