OmniSci
Overview
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HQ Location
United States
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Year Founded
2013
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Company Type
Private
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Revenue
< $10m
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Employees
51 - 200
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Website
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Company Description
OmniSci is the pioneer in accelerated analytics. The OmniSci platform is used in business and government to find insights in data beyond the limits of mainstream analytics tools. Harnessing the massive parallelism of modern CPU and GPU hardware, the platform is available in the cloud and On-Premise. OmniSci originated from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). OmniSci is funded by GV, In-Q-Tel, New Enterprise Associates (NEA), NVIDIA, Tiger Global Management, Vanedge Capital and Verizon Ventures. The company is headquartered in San Francisco. Learn more about OmniSci at www.omnisci.com.
IoT Solutions
Accelerated Analytics Platform
Accelerated Analytics Platform
The OmniSci platform is designed to overcome the scalability and performance limitations of legacy analytics tools faced with the scale, velocity and location attributes of today’s big datasets. Those tools are collapsing, becoming too slow and too hardware-intensive to be effective in big data analytics.
OmniSciDB
Open source SQL engine
The foundation of the platform is OmniSciDB, the world’s fastest open-source, analytics database. OmniSciDB harnesses the power of GPUs and CPUs and returns SQL query results in milliseconds, even on tables with many billions of rows. OmniSciDB delivers that extreme big data analytics performance with a combination of support for native SQL, rapid query compilation, query vectorization and advanced three-tier memory management.
OmniSci Render
Server-side visual rendering
OmniSci Render is a server-side engine designed for rendering pointmap, scatterplot and polygon visualizations of massive datasets. This gives users zero-latency, exploratory interaction with complex visualizations, something never before possible. For geospatial visualization, the Vega rendering engine API allows users to visualize up to billions of points, lines, or polygons.
OmniSci Immerse
Interactive visual analytics
OmniSci Immerse is a web-based data visualization interface, leveraging the accelerated speed and rendering capabilities of OmniSciDB and OmniSci Render for unparalleled visual interaction. OmniSci Immerse is incredibly intuitive and easy to use, providing standard visualizations, such as line, bar, and pie charts, as well as complex data visualizations, such as geo-point maps, geo heat maps, choropleths, and scatter plots. Dashboards automatically cross-filter when interacting with data, and refresh with zero latency.
Data Integration
Connecting data sources to OmniSci
OmniSci open sourced the OmniSciDB SQL engine to make it easy and effortless for users and developers to accelerate analytics and Data Science workloads. OmniSciDB is available on GitHub under the Apache 2.0 license, alongside other components like a Python interface (pymapd) and JavaScript infrastructure (omnisci-connector, omnisci-charting), making OmniSci the leader in Open Source accelerated analytics.
Accelerated Analytics Platform
The OmniSci platform is designed to overcome the scalability and performance limitations of legacy analytics tools faced with the scale, velocity and location attributes of today’s big datasets. Those tools are collapsing, becoming too slow and too hardware-intensive to be effective in big data analytics.
OmniSciDB
Open source SQL engine
The foundation of the platform is OmniSciDB, the world’s fastest open-source, analytics database. OmniSciDB harnesses the power of GPUs and CPUs and returns SQL query results in milliseconds, even on tables with many billions of rows. OmniSciDB delivers that extreme big data analytics performance with a combination of support for native SQL, rapid query compilation, query vectorization and advanced three-tier memory management.
OmniSci Render
Server-side visual rendering
OmniSci Render is a server-side engine designed for rendering pointmap, scatterplot and polygon visualizations of massive datasets. This gives users zero-latency, exploratory interaction with complex visualizations, something never before possible. For geospatial visualization, the Vega rendering engine API allows users to visualize up to billions of points, lines, or polygons.
OmniSci Immerse
Interactive visual analytics
OmniSci Immerse is a web-based data visualization interface, leveraging the accelerated speed and rendering capabilities of OmniSciDB and OmniSci Render for unparalleled visual interaction. OmniSci Immerse is incredibly intuitive and easy to use, providing standard visualizations, such as line, bar, and pie charts, as well as complex data visualizations, such as geo-point maps, geo heat maps, choropleths, and scatter plots. Dashboards automatically cross-filter when interacting with data, and refresh with zero latency.
Data Integration
Connecting data sources to OmniSci
OmniSci open sourced the OmniSciDB SQL engine to make it easy and effortless for users and developers to accelerate analytics and Data Science workloads. OmniSciDB is available on GitHub under the Apache 2.0 license, alongside other components like a Python interface (pymapd) and JavaScript infrastructure (omnisci-connector, omnisci-charting), making OmniSci the leader in Open Source accelerated analytics.
IoT Snapshot
OmniSci is a provider of Industrial IoT platform as a service (paas), application infrastructure and middleware, analytics and modeling, and networks and connectivity technologies, and also active in the automotive, oil and gas, and telecommunications industries.
Technologies
Functional Areas
Industries
Services
Technology Stack
OmniSci’s Technology Stack maps OmniSci’s participation in the platform as a service (paas), application infrastructure and middleware, analytics and modeling, and networks and connectivity IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.
Case Study
Leveraging IoT for Enhanced Network Analytics: A Case Study on TELUS and HEAVY.AI
TELUS, a leading telecommunications company, was faced with the challenge of interactively exploring complex network datasets without experiencing lag. The company needed a comprehensive mapping of TELUS communities and competitor speed information to better understand the market dynamics. Identifying competitor coverage and deciding where to build wireless services was another significant challenge. Each of TELUS’s high-speed services has its own coverage layers, qualification criteria, and competitive restrictions. TELUS Marketing needed to know where they could deploy each service, the targeting potential, and where competitors offer similar services. They required an advanced analytics solution that quickly shows their customer base, potential upsell opportunities, and where wireline and wireless high-speed internet adoption are low.
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