GPU-accelerated analytics database
for real-time insights on large and streaming datasets

Kinetica harnesses the power of GPUs for unprecedented performance to ingest, explore and visualize data in motion and at rest.

Proven at Enterprise Scale

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GPU hardware acceleration is revolutionizing high performance computing. Kinetica's GPU database is redefining what is possible with data and analytics.

Incredibly Fast

The GPU parallelized processing architecture not only enables near-linear scalability, it also reduces analytical processing times for multi-billion row data sets by more than 100x compared to leading in-memory and analytical databases.

Aggregate Queries Leading In-Memory DB > 50x Slower NoSQL DB’s > 100x Slower Time for an aggregate of queries (s) Less is better!

Artificial Intelligence and Business Intelligence CONVERGED ON A GPU-ACCELERATED DATABASE

GPUs are well suited for the types of vector and matrix operations found in machine learning and deep learning. In-database processing on Kinetica opens the way for machine learning and artificial intelligence libraries such as TensorFlow, BIDMach, Caffe, Torch and others to work directly on data within Kinetica.

Converged AI and BI

Now AI workloads can run together on the same GPU-accelerated database platform as BI operations. Doing so makes it possible to quickly deploy new models and eliminates the time and effort required to transform data and move it back and forth between a database and a separate data science system.

Ideal for Location-Based Analytics

Kinetica comes with a native geospatial and visualization pipeline for rendering large volumes of data over maps. This makes Kinetica particularly well suited for fast moving, location-based IoT data. Kinetica includes Reveal – an extensible and flexible web-based analytics visualization framework. You can also connect Kinetica to other BI tools such as Tableau and MicroStrategy via ODBC/JDBC.

Distributed In-Memory Architecture

Kinetica is a distributed, columnar, relational database designed for analytics on large and streaming datasets. Tiered memory management allows data to be held in VRAM and system memory, with persistence to disk.

SQL, REST API, and more...

Kinetica's SQL query capabilities enable business users to be immediately productive without learning new languages or systems. The native REST API and associated connectors provide data scientists a robust tools for interacting from Python, Node, Java, C++ and more.

Secure with High Availability

Enterprises rely on Kinetica's mature security model and high-availability architecture for mission-critical workloads. Multiple replicas of data eliminate single points of failure, and provide an eventually consistent data store with recovery capability.

GPU Data Analytics eBook
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See How GPUs are Defining the Future of  Data Analytics

Developed to meet the intelligence needs of the US Army

Kinetica was built to meet the needs of US Army Intelligence and Security Command—to track and analyze terrorist and other national security threats in real time. The solution was launched within the military in 2012 and was made commercially available in 2014.

It’s literally battle tested.

Case Studies & Use Cases »

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Take the Kinetica Challenge!

Sometimes benchmarks and marketing copy can sound too good to be true. The best way to appreciate the possibilities that GPU acceleration brings to large-scale analytics is to try it with your own data, your own schemas and your own queries.

Contact us, and we'll set you up with a trial environment for you to experience it for yourself.