An overview of the concept of kdb+ frameworks
A blog exploring three approaches to market data analysis with KDB.AI
Maintaining direction and quality in time series data in a dynamic and challenging environment
A brief comparison of anomaly detection with KDB.AI vs a traditional approach, MASS.
A guide to running TorQ on Amazon FinSpace with Managed kdb Insights
How can we streamline the data capture pipeline when our appetite for data outweighs our hardware resources?
Phase 1 of incorporating AI, KDB.AI, LangChain and ChatGPT to improve support coverage and productivity in Data Intellect
A full kdb+ Managed Service, enabling clients to focus on their business. It is powered by our industry partnerships, thought leadership, technology and data expertise.
Explore the potential of large language models (LLMs) in data querying and creative problem-solving with our hands-on, real-world examples.
A look into using ChatGPT along with kdb+ as a developer
At AquaQ we often are tasked with providing independent insight into our clients' kdb+ architecture which usually results with our ARK (Architecture Review of kdb+), but…
When investors want to define or use a new trading strategy, they need a method to verify its expected performance. One method for achieving this is…