GPU database for IoT - A silver bullet to manage your IoT data and analytics tsunami

Data analytics has changed dramatically over the last decade. We started with traditional RDBMS and distributed storage, and moved to advances in in-memory analytics with NoSQL. Today, GPUs are powering the next generation of data analytics and compute, bringing high-performance computing and real-time analytics to industry-standard hardware–and enabling new enterprise solutions such as IoT.

In this talk, I’ll show you how GPU-accelerated computing gives you the ability to complete an aggregate query against a table with 4 billion records in 250ms or less. Complex aggregates that require table scans can now be performed in a fraction of the time. You’ll also learn how you can easily take advantage of and implement into your existing infrastructure, with comprehensive integration with the Hadoop ecosystem (Kafka, NiFi, Storm, Spark) and with common BI and SQL tools (Tableau, Kibana and Caravel), fully supported APIs (REST, C++, Java, Python, JavaScript, Node.js), native visualization and geospatial capabilities , and NLP-based full-text search.