GPU hardware acceleration is revolutionizing high performance computing. Kinetica's GPU database is redefining what is possible with big data.
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.
Use Less Hardware
In the world of big data, processing often becomes the bottleneck. Kinetica's GPU architecture addresses this problem with dramatic efficiency gains. Kinetica customers on average require just 1⁄10 of the hardware and 1⁄20 of the power.
Ingest from a torrent of data
Stream and analyze data in real time. Kinetica plugs into existing data architectures and can connect to feeds using Apache Kafka, Apache Spark, Apache NiFi and commercial connectors.
No More... Indexing
Kinetica's GPU architecture is well suited to brute force processing of data. Say goodbye to reindexing, partitioning, downsampling and waiting! Kinetica is a SQL-compliant database enabling business users to get to work without learning new languages or constructing new data models.
Kinetica's visualization tools render large volumes of data on the fly, and are particularly well suited for fast moving, location-based IoT data. You can also connect Kinetica to open source tools such as Kibana and Caravel, or to BI reports and dashboards via ODBC/JDBC.
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.