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HEAVY.AI
Data Analytics
HEAVY.AI, formerly known as OmniSci and originally MapD, is a San Francisco-based analytics database company that uses GPU acceleration to let analysts run extremely fast queries and visualizations over very large datasets.
$338M
+$1.09
9.70%
30 days ago
$11.22
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HEAVY.AI traces its origins to 2013, when it was founded as MapD by Todd Mostak, a researcher who had grown frustrated with how slowly traditional database systems could query and visualize very large datasets while conducting his own academic research analyzing large volumes of social media data, motivating him to explore whether graphics processing units (GPUs), which had already proven dramatically faster than traditional processors for certain kinds of parallel computation in other domains, could be applied to dramatically speed up database query processing and interactive data visualization, particularly for datasets involving geographic and time-series data where traditional databases often struggled to deliver interactive-speed query responses at large scale. The company's core database technology uses GPU acceleration to process queries and render visualizations over very large datasets, including billions of rows, at speeds the company argues are often dramatically faster than traditional CPU-based database systems, letting analysts interactively explore and visualize massive datasets, such as detailed geospatial data or high-frequency time-series data, with the kind of fluid, real-time interactivity that would be impractical using conventional database technology at similar data scale. The company rebranded from MapD to OmniSci in 2018 and subsequently to HEAVY.AI in 2022, reflecting an evolving positioning that has increasingly emphasized the platform's applicability to AI and machine learning workloads involving very large datasets, in addition to its original core strengths in fast geospatial and time-series analytics and visualization. HEAVY.AI's customers have included government agencies, telecommunications companies, and other organizations working with very large-scale geospatial or time-series datasets where query and visualization speed at scale is a significant operational requirement, such as analyzing large volumes of network telemetry data or geographic movement data. The company has raised venture funding from investors including Verizon Ventures, Nvidia, and In-Q-Tel, the latter reflecting government and intelligence community interest in its large-scale geospatial analytics capabilities, competing with other GPU-accelerated and large-scale analytics database vendors.
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