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Kx adds ChartIQ to visual dashboard

18 July 2017  |  2506 views  |  0 Source: Kx

Kx Systems (Kx), a division of First Derivatives plc (FD) and provider of the industry-leading kdb+ time series database, announces today that Dashboards for Kx now offers ChartIQ integration as an optional addition to its visualization capabilities.

Dashboards for Kx is a real-time data visualization platform built on HTML5 and optimized for high volume, high velocity streaming data. Dashboards enables analysts, business users and consumers of large data to define complex interactive queries, create views and monitor trends and identify risk thresholds in real time.

ChartIQ is a feature-rich financial charting and visualization solution, trusted by the largest firms in finance. ChartIQ offers end users a highly immersive and interactive charting experience; merging dynamic visualization of financial data with the performance and power to handle Big Data. ChartIQ’s HTML5 Charting Library is pure JavaScript and entirely browser-based, supported on all modern browsers, and easily accessed and deployed on desktop, tablet and mobile devices.

Dashboards for Kx offers ChartIQ as a fully integrated component, and combines ChartIQ’s visualization with Dashboards’ built-in data access that includes streaming and comprehensive configuration control for optimum performance. Designers can create dashboards linking interactions with a full suite of components and build the most sophisticated UI with financial data.

When integrated with Kx technology, ChartIQ benefits from lightning quick data processing where timing is critical in delivering results. Kx technology processes and analyzes high volumes of streaming, historical and real-time data at runtime, with an in-built memory database kdb+ and a unique programming language q. In the era of Big Fast Data analytics, kdb+ has set industry benchmarks for speed and stability across a wide range of markets, including in the manufacturing and retail sectors, which now have to address more demanding data challenges.

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