A framework for creating interactive, details-on-demand data visualizations that scale to millions of records with a declarative API.
Kyrix is a framework for creating interactive, details-on-demand data visualizations that scale to large datasets. It solves the problem of building performant, pan-and-zoom enabled visualizations for millions of data records by providing a declarative API and a containerized database backend.
Visualization developers and data engineers who need to build interactive, large-scale data visualizations with smooth pan/zoom interactions and details-on-demand capabilities.
Developers choose Kyrix for its combination of a declarative authoring grammar that simplifies specification, a dockerized setup that removes database management overhead, and a focus on sub-second response times for interactive browsing of big data.
Interactive details-on-demand data visualizations at scale
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Offers both low-level expressive and high-level Kyrix-S grammars, simplifying specification of complex visualizations like the NBA scatterplot example with concise code.
Provides a fully containerized PostgreSQL database, eliminating installation and maintenance hassles while scaling to 10-100 million records without manual database management.
Includes APIs for embedding visualizations into existing web apps, enabling coordinated views and programmatic control as documented in the wiki.
Focuses on achieving 500ms response times for pan/zoom interactions, ensuring smooth browsing of large datasets as highlighted in the performance goals.
Current beta version only supports up to 10-100 million records and lacks distributed processing, with a future version planned for larger datasets.
Marked as research-quality code with a disclaimer against use in secure, production environments, indicating potential stability and security issues.
Kyrix-S grammar is optimized for zoomable scatterplots, making other visualization types more cumbersome to implement with the verbose low-level API.