kdb+ Reviews and Ratings

Rating: 9 out of 10

Score

9 out of 10

Community insights

TrustRadius Insights for kdb+ are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

Comprehensive Analytics Solution: Users find KX's streaming analytics, data and analytics capabilities in a single solution to be unique and comprehensive. This has been mentioned by several reviewers who appreciate the convenience of having all their analytical needs met in one platform. Ease of Use: The solution is praised for its ease of use, with users stating that analysis is simple, fast, and easy to share. Many reviewers have found the platform user-friendly and intuitive, allowing them to quickly perform complex operations without much effort. Efficient Handling of Time Series Data: Users appreciate KX's ability to handle intricate time series transformations on large amounts of data efficiently. Several reviewers have specifically highlighted this feature as a strong point of the platform, enabling them to work with time series data effectively. Overall, reviewers have consistently praised KX for its comprehensive analytics capabilities, ease of use, and efficient handling of time series data.

Reviews

5 Reviews

Scalable and Reliable

Rating: 9 out of 10

Incentivized

March 29, 2022

Use Cases and Deployment Scope

We use it for large-scale data collection, storage, analysis, and modeling. It has been game-changing in our ability to conduct research on large-scale datasets and has sped up our research pipeline and ability to share code across the team. This is for basic queries as well as more sophisticated AI work.

Pros

Time series analysis.
Large dataset storage.
Query re-use.

Cons

Run time error message readability, particularly for new users.
Backwards compatibility between versions.

Likelihood to Recommend

Great for research and storage, less so for running production code to generate outputs for financial markets decisions.

Verified User

Strategist in Research & Development (10,001+ employees)

Vetted Review

10 years of experience

KDB+ for real time tick data and analytics

Rating: 8 out of 10

Incentivized

January 8, 2016

Use Cases and Deployment Scope

I work in the equities area, where we use kdb for most of our real time tick data requirements. Tick data in our case ranges from market data, real time analytics, live PNL and orders data etc.

Pros

It is really fast if chosen for the right problem.
Large logic can be shrunk into a tiny snippet.
It provides a column oriented database, where each column in a table is a vector. Thus you can perform very fast analytics using its vector processing power.

Cons

It is sometimes painful to accept the fact that KDB+ is not fully multithreaded.
The ability to write shorter code for a complex logic is really good. But it makes it really cryptic. Cryptic codes are very difficult to maintain and extend.
For some small institutions license cost is little high.

Likelihood to Recommend

kdb is well suited for real time tick data and time series analytics.

ROHAN MANE

AVP in Information Technology at Citi (10,001+ employees)

Vetted Review

7 years of experience

View profile

kdb+ is always ahead of its time

Rating: 10 out of 10

Incentivized

January 5, 2016

Use Cases and Deployment Scope

I've been using kdb+ in the context of storing and generating analytic from large financial data set for over 10 years. IMHO, no other product provides the performance and flexibility remotely close to kdb+. The build-in language q is very terse and expressive. In one of my former jobs, traders were creating new quantitative models almost "in the speed of thoughts" with kdb+. That really gave us the edge of "time to market".

Pros

Time series analysis. The built-in vector operations are extremely fast. Also with the q language you can code up any customized analytical ideas quickly.
The database are all file based, very easy to maintain.
Very solid and fast interface to websocket, so you can interface with javascript easily.

Cons

The learning curve is a little steep in the beginning.

Likelihood to Recommend

When you are dealing with large scale time series data, [there are] no better alternatives. I've seen some firms use other so called "big data" alternatives, and claim they can store the data just as efficiently. However, once you want to generate sophisticated analytics from the data, nothing beats kdb+.

Ye Tian

Quant Strategist at KCG Holdings, Inc. (1001-5000 employees)

Vetted Review

10 years of experience

View profile

Powerful language

Rating: 6 out of 10

Incentivized

December 14, 2015

Use Cases and Deployment Scope

kdb+ is very useful in the trading world as it allows analysts to look at huge amounts of data quickly and somewhat easily. Speed was a huge factor.

Pros

Efficient computing.
Code interpretation is fast.
Designed with finance in mind.

Cons

The language is difficult to learn.
Better solutions are needed for breaking loops without resetting servers.
Include basic templates for fields such as finance, medicine, etc.

Likelihood to Recommend

For large data sets, kdb+ is very tough to beat, however it is not user friendly to pick up and use on the go.

Verified User

Analyst in Research & Development (501-1000 employees)

Vetted Review

1 year of experience

Fast but hard to implement

Rating: 8 out of 10

Incentivized

December 8, 2015

Use Cases and Deployment Scope

We use kdb to store and analyze real time market data for transaction cost analysis.

Pros

Process large amounts of time series data
Perform quick calculations without use of cursor
Use of window joins and as of joins

Cons

Hard to read
Hard to find knowledgeable developers
Lack of good IDE

Likelihood to Recommend

It is best for large data sets that have one common index across multiple tables.

Verified User

Strategist in Research & Development (201-500 employees)

Vetted Review

2 years of experience

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