Kx for Automotive is a high-performance, cost-effective data platform for ingesting, processing and analyzing real-time, streaming and historical data from multiple sources in the automotive world - data that fuels future business models and innovations.

From trackside telemetry in F1, to R&D and aerodynamics in wind tunnels, from autonomous cars in motion to their digital twins in simulation, from the sensors that control them to the machines that make them, Kx for Automotive has the power and scalability to provide real-time analytics, instantaneous feedback and valuable insights into the vast amounts of data they produce.

Watch the video to discover why Aston Martin Red Bull Racing use Kx technology.

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"Kx helps us because it allows us to gather huge streams of data, in real-time, to analyse that data very quickly, and to make decisions when seconds count.”

Matt Cadieux, Chief Information Officer, Aston Martin Red Bull Racing


Data requirements in the automotive industry are particularly challenging, not only in terms of volume and latency, but also in terms of the reliability and precision necessary to deliver both high-performance and safety on road, track and production line. Electric vehicles, Advanced Driver Assistance Systems (ADAS), traffic services and 5G connectivity will simply add to the deluge of data the industry must accommodate. Kx for Automotive can handle these volumes with ease and provide unparalleled response time to queries and analytics.  The solution is powered by Kx, the world’s fastest time-series database.

Kx can capture, store and process millions of events and measurements per second, gigabytes to petabytes of historical data with nanosecond precision, more efficiently and cost-effectively than any available alternatives. Proven across many industries, from finance to high tech manufacturing, Kx is the standard for time-series data management and processing.

“Time series data is the data and information that we acquire from sensors, that might be attached to a wind tunnel model, or indeed a race car. It’s a difficult problem to solve because the sensors acquire a lot of data in a very short space of time. When we started to think about how we were going to solve this problem in our next-generation system for the wind tunnel, we took a look at what the financial services industry did to solve the same problem with market data. When we searched the market, Kx stood out as the industry leader.”

Daniel Hurst, Aero Technology Development Team Leader, Aston Martin Red Bull Racing


It is estimated that 90% of new cars will be connected by 2020. That means digital connectivity both within cars and across the full ecosystem of vehicles in motion. Add to that the focus on electric vehicles, electronic powertrains and shared vehicles with their output from sensors, cameras, radar, and LIDAR, and it is clear that there will be a corresponding increase in data volumes.

In cars alone, estimates range from 25 GB per hour in the currently connected vehicles of today to 4 terabytes per day in the fully autonomous ones of tomorrow. Estimates may vary but the necessity to capture, process and analyze this data in real-time does not change.

Kx for Automotive provides a solution for the flood of data to be managed:
  • Its low footprint enables in-vehicle deployment that reduces message latency in order to achieve the real-time, instantaneous processing required for vehicles in motion
  • Its unparalleled scalability easily accommodates centralized cross-vehicle consolidation of data to enable industry-wide analysis across all data dimensions


The ever-increasing number of connected devices, sensors, camera and tags in the automotive manufacturing process is creating a colossal amount of data for organizations to process, analyze and store. Most current manufacturing execution systems struggle with the bottlenecks which emanate from this new abundance of data. Their limitations inhibit the opportunity to exploit the rich value of that data in areas like fault detection, root cause analysis, and predictive maintenance.

Kx, with its superior columnar-structured time-series database, and its integrated query language q, enables you to scale from thousands up to hundreds of millions of sensors at any measurement frequency whilst maintaining extremely high levels of performance.

  • Ingest and process 4.5 million sensor measurements and events per second per core
  • Aggregate billions of measurement records in seconds
  • Store and analyze trillions of records
  • Scale both vertically and horizontally


The growing volume of data in automotive environments provides new opportunities for predictive analytics and operational efficiencies in all areas from design and development to automation and supply chain management.

Kx for Automotive can capture, analyze and store high-frequency time-series data from thousands of sensors to compare with historical data in areas like fault detection and anomaly analysis. It includes a comprehensive suite of graphical tools with powerful OLAP drill-down capabilities to aid decision making based on historical and real-time data from multiple data streams.

Our technology platform can be used to analyze data from wind tunnels, trackside, roadside and satellite to assess performance, identify faults, predict potential failures, plan maintenance to improve design, optimize performance and reduce cost.

“The Kx software stack delivers a modern data platform, one that fuses the latest industry paradigms, such as streaming, messaging and complex event processing, with the ability to handles huge amounts of time series data, all in real-time. ”

Daniel Hurst, Aero Technology Development Team Leader, Aston Martin Red Bull Racing



The Kx for Automotive solution is built on an enterprise data management platform that supports both the data and the processing environment for Machine Learning. It provides out-of-the-box interfaces to popular machine learning tools such as TensorFlow, Theano and Keras as well as tools like embedPy that enable continued use of existing libraries written in Python. Armed with data and ML capabilities Kx for Automotive supports AI initiatives around fleet learning, safety/ADAS analysis, simulated tests and predictive collision avoidance.

  • Combine historical and real-time data for fault and anomaly detection, and make more timely and accurate predictions
  • Analyze data from millions of devices and connected cars order to forecast consumption, detect anomalies, predict failures
  • Analyze data from assets to identify faults, predict potential failures and plan maintenance


Kx technology integrates with legacy systems and multiple data sources, allowing you to either augment or replace existing systems and libraries

  • A connector framework simplifies integration and coexistence with incumbent systems
  • APIs for .NET, Java, C, C++, Python, R, ODBC, Matlab and Excel.
  • Machine Learning capabilities using embedPy which loads Python into kdb+, allowing access to a rich ecosystem of libraries such as scikit-learn, tensorflow and pytorch

The kdb+ time-series database, at the core of Kx Technology, is renowned for its computational speed and performance, as well as the simplicity of its architecture for large-scale data analytics.

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