Your data is only as powerful as your platform.
Analyze and act on it with Kinetica.
Load and analyze
Data, analytics, location intelligence, and ML in one platform
Analyze your entire
collection of data
More Than A Traditional Data Warehouse
Kinetica combines historical and streaming data analysis with powerful location intelligence and AI in a single platform, all easily accessible via API and SQL, for instant results.
Solving Impossible Problems
The Kinetica Streaming Data Warehouse delivers up-to-the-second results that incorporate all your data in a powerful, unified platform. Stream and analyze simultaneously for real-time results, and apply cutting-edge location intelligence and machine learning-powered predictive analytics.
Act on data in real time to track and detect national security risks and cyber threats, optimize logistics and mobilize supply chains, upgrade infrastructure, and protect public safety and more.
Leverage real-time and predictive analysis to inform network coverage planning, blend large, complex geospatial datasets to dynamically visualize infrastructure at scale, and project ROI with high accuracy across geographies.
Power real-time trade and risk decisioning applications that increase revenue and improve compliance, and modernize and simplify analytics infrastructure to keep up with the speed, scale, and complexity of financial data.
Optimize operations across the logistics network with real-time ingestion, visualization, and analysis of fast-moving data, from vehicle IDs to location, personnel, weather, traffic, and supply and demand data.
Solutions for Every Customer
Whether you’re the Chief Data Officer or the VP of Analytics, purchasing data analytics technologies is fraught with risk, from latency to scalability, accuracy to complexity. Choose the right platform.
You’re planning for the future evolution of your stack, and your design and investments have to make sense for the long-term stability of your architecture, without locking you in.
Different components lead to complexity. But if you combine capabilities, then you can build and manage data pipelines to get data where it’s needed, when it’s needed.
Developing analytics applications for data processing, exploration, and visualization should be as fast and easy as possible, so you spend your time writing code, not building data pipelines.
OVO SmartCube is designed to evaluate customer preferences using analytics powered by a machine learning-enabled recommendation engine, which makes product suggestions. Powered by Kinetica, the machine can also provide instant assessments of when and what purchases take place, in order to offer relevant deals.
GSK uses Kinetica to speed up vaccine development,
a process which normally takes six to eight years, by taking billions of rows of data and processing at a speed and scale that can ultimately bring new medicines to market faster.
SFEI uses drones to collect thousands of images of the San Francisco Bay, which they feed into a Kinetica-powered machine learning algorithm to detect trash - a process that has gone from days to just hours, so we can identify pollutants and take immediate action.