Hi, CEO of MapD here. I agree that while some users don't need this level of speed, many do. Hadoop use cases are often very different than those that demand t

Hi, CEO of MapD here. I agree that while some users don't need this level of speed, many do. Hadoop use cases are often very different than those that demand the speed of in-memory processing for real time answers. Think about all the money going into high-performance solutions like Spark, HANA, Vertica, Redshift, Exadata, MemSQL, etc. And many use cases demand even more speed, which is where GPU acceleration comes in. We just launched this year but already are being used in telco, hedge fund, social media, adtech, defense and retail deployments, with many more on the way. Most of our customers have been inbound, motivated by a common pain point of not having real-time visibility into their datasets. For example, Hadoop would not be acceptable for our use cases at Verizon, where troubleshooting needs to occur in real-time and not with lags measured in hours. I'm a firm believer in horses for courses. Not everyone needs the fastest tech, but for those that do, it makes all the difference.