Kx for Data as a Service (DaaS)

The Kx for DaaS software platform brings together all of the hard-won experience and battle-hardened technology developed by Kx for financial markets into a platform that can be used for real-time and historical data capture and analytics across any business vertical. Kx is no longer just about financial markets.

Kx for DaaS provides a complete suite of tools for managing data from ingestion through consumption by multiple parties in a consistent and controlled manner. Built on Kx technology, our DaaS solution delivers the speed and performance Kx is known for.

Simplifying Data Management

DaaS is a high-performance low-latency data processing platform providing flexible real-time access to time-series data and powerful analytics. It is designed to take the data management and processing burden away from the user and let them concentrate instead on exploiting its potential.

Fast and Powerful

DaaS is an easy to use interactive platform enabling users to execute queries and get responses in milliseconds, not hours.

It is developed on a single integrated software stack for quicker, easier implementation, lower cost and reduced TCO.

Ease of Use

For non-technical users DaaS offers an intuitive interface that enables them to form queries simply by stating what data they want and the parameters for calculating their results. Users do not need to know about query languages or schemas, they can focus instead on what they really want - the data. Advanced users can use Kx's programming language q for more complex queries.

Comprehensive
  • All asset classes supported
  • Level 1 and level 2 data
  • Historical symbology management
  • Corporate action adjustments
  • Cancellations and corrections
  • Time zone management
  • Nanosecond time stamping
Lambda Architecture

DaaS is built on an HTAP architecture that combines in-memory computing, low-latency messaging and streaming capabilities that enable it to perform time-series operations on both real-time and historical data seamlessly. Sample financial applications include: order replay for best execution and TCA analysis, back testing data for new algorithms and ad hoc queries across the full sweep of historical data.