This podcast by Brian from QuantLabs.net dives into the world of High-Frequency Trading (HFT) and the role of KDB+ in this domain. KDB+: Developed by KX, KDB+ is a high-performance software used for data handling in HFT. It excels at working with large time-series datasets and is known for its: Efficiency Uncomplicated code structure Python integration Cloud interoperability KDB+ and Ticker Plant: Ticker Plant can be used to feed data into KDB+, making it a popular combination for HFT applications. Cost: A major barrier to entry for KDB+ is its high cost, estimated to be around $100,000 per year. This limits its use primarily to the well-funded fintech industry. Future Potential: Despite the cost, KDB+ remains a dominant player due to its performance and features. Brian discusses the potential of KDB+ to evolve even further with advancements in technology and AI. Call to Action: Brian invites listeners to join his Discord community to discuss KDB+ and related topics. Exploring the Power of KDB+ for High-Frequency Trading and Data Analytics - QUANTLABS.NET Welcome everyone, Brian from QuantLabs.net is here with another intriguing episode. In this episode, Brian dives deep into the world of High-Frequency Trading and advanced data analytics, emphasizing the role of KBD+ in it. Touching upon a previous episode of the podcast on the same topic, he delves into the intricacies of software like the Ticker Plant. Brian explains that KDB+, produced by KX, is a high-standard enterprise-level software known for its efficient data handling capabilities. As he deconstructs the workings of this software, he highlights how Ticker Plant could write all incoming records to a log file, pushing all data to the RDP. This software, although widely unknown, is an industry standard. The focus then shifts to the price aspect of KDB+, and the barriers it poses for widespread market adoption. Discussing a comment on Hacker News, Brian brings to light the exorbitant cost of KDB+, estimated at around a hundred thousand dollars per year. As per the comment, software is extremely lucrative and can only be afforded by the fintech industry. Despite the cost, KDB+ comes highly praised. A comment Brian brings up highlights KDB+ as an elegant solution for running analytics on large data sets, especially those with time series. Known for its performance, uncomplicated code structure, Python integration, and cloud interoperability, KDB+ has been a dominant player in electronic trading analytics on Wall Street for over 20 years. In conclusion, Brian discusses the potential of KDB+, which opens avenues for potential business opportunities. He emphasizes how innovations in technology and AI could lead to exploring beyond the limitations imposed by network cards. Following his exploration of KDB+ and its potential, he invites listeners to join his Discord community and actively engage in stimulating discussions.   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack