GPU database – designed from the ground up
to deliver truly real-time insights

GPU acceleration changes the game for fast data analytics, for location-based analytics and for predictive analytics

GPU Processor

GPUs are designed around thousands of small, efficient cores that are well suited to performing repeated similar instructions in parallel. This makes them well-suited to the compute-intensive workloads required of large data sets.
Some of the latest high performance GPUs from NVIDIA feature over 4,000 cores, versus 16 to 32 cores per typical CPU-based device.
GPU cores crunch data far more efficiently and quickly than CPUs—which process data sequentially.
Why Another Database? PLAY

So much raw compute power, you won't need to think about indexing, partitioning or downsampling!

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Very Low Latency

With less to index, data is available immediately after it is written. No more waiting for data structures to be updated before the data can be returned in queries.

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Ask any question

Since there is no need to prepare the schema before it can be explored, business analysts have complete flexibility and freedom for data discovery projects.

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Linear Scale out

With simpler data structures, the database scales in proportion to the size of the data. This leads to smaller and more predictable hardware costs.

Did we mention speed?

10x-100x faster than even the most advanced in-memory databases

In tests, Kinetica returns results for advanced analytical queries on billions of rows of data in well under a second.

HANA

GPU benchmarks Legend

Price/Performance : Download the White Paper »

Scale out on industry-standard hardware

The efficiencies of Kinetica's GPU architecture typically result in hardware costs that are 110 that of other in-memory databases.

As datasets grow, Kinetica is able to scale out across multiple nodes. Kinetica leverages the raw compute power of the GPU to break open processing bottlenecks and reduce reliance on indexes. In addition to performance benefits, customers experience dramatic efficiency gains. Kinetica sometimes requires just 1⁄10 of the hardware and 1⁄20 of the power when compared to other in-memory analytics solutions.

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Kinetica runs on commodity hardware, that scales out linearly to meet your needs.

Certified to run on premise with:

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Or in the cloud:

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Accelerated By
NVIDIA partnered with Kinetica

Set Business Users Free!

Kinetica provides a range of methods for analysts and line of business users to query across the full dataset. The raw power of GPU-accelerated analytics ensures there is no need for partitioning, downsampling, or redesigning the data model when a new query capability is needed.

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Full Text Search

Full text search functionality is supported by Natural Language Processing (NLP) and the full set of results can be rendered on a map. Results aren’t limited to the first 10, 20 or 30 pages of relevant information.

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Write Queries in SQL

Kinetica is a fully SQL compliant database; no programming necessary. Query your data the way you want to.

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Use with Popular BI Tools

ODBC/JDBC connectors ensure data can be used with popular BI tools such as Tableau and open source front-end tooling such as Kibana and Caravel.

Kinetica Reveal : Visualization Framework

Bring your own BI dashboard, or take advantage of Kinetica 'Reveal' — a web-based visualization framework that makes it easy to slice, dice and visualize data in Kinetica. Reveal works with Kinetica's native geospatial visualization pipeline to make it possible to see changes across large datasets as the underlying data or queries change.

  • Allow users to easily and intuitively visualize datasets, and share interactive dashboards
  • Visualize billions of data points on a map, filter and query them with real-time response.
  • Take advantage of a wide gamut of geospatial visualization renderers such as feature, class break, heat maps, and geofencing.

Find out more about Reveal »

Kinetica Visualization Demo
Kinetica is able to render billions of points on a map in under a second. Learn More »

Try Out Kinetica Today!

Try Kinetica, with Reveal – our flexible visualization framework. A selection of live data feeds including Twitter, FAA flight data, and taxi data can be queried on a 4 node Kinetica cluster.

Power and capability for developers and administrators

Ingest from multiple sources

Pre-built connectors for Apache Kafka, Apache NiFi, Apache Spark, Spark Streaming, Apache Storm, and ODBC/JDBC make it simple to ingest data from a wide range of data sources.
See Examples »

Scale out

Kinetica provides linear scalability on industry standard hardware. Data replication is handled for high availability. Sharding can be done automatically, or specified and optimized by the user.

Comprehensive APIs

Kinetica can easily be interacted with via RESTful HTTP endpoints. Supports both JSON and Avro serialization. Open source native language bindings can be found for Java, Python, Javascript, and C++. More »

Architecture w/UDFs

Advanced Analytics with In-Database Processing

User-defined functions (UDFs) enable compute as well as data-processing, within the database. Kinetica uniquely offers such functionality on a database that fully utilizes the parallel compute power of the GPU.
In-Database Processing Brings AI and BI Together »

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.