Editor’s note: Today, we hear from our partner MapD, whose data analytics platform uses GPUs to accelerate queries and visualizations. Read on to learn how MapD and Google Cloud are working together.
MapD and public cloud are a great fit. Combining cloud-based GPU infrastructure with MapD’s performance, interactivity and operational ease of use is a big win for our customers, allowing data scientists and analysts to visually explore billion-row datasets with fluidity and minimal hassle.
Our Community and Enterprise Edition images are available on AWS, MapD docker containers are available on NVIDIA GPU Cloud (NGC), as well as our own MapD Cloud. Today, we’re thrilled to announce the availability of MapD on Google Cloud Platform (GCP) Marketplace, helping us bring interactivity at scale to the widest possible audience. With services like Cloud DataFlow, Cloud BigTable and Cloud AI, GCP has emerged as a great platform for data-intensive workloads. Combining MapD and these services let us define scalable, high-performance visual analytics workflows for a variety of use cases.
On GCP, you’ll find both our Community and Enterprise editions for K80, Pascal and Volta GPU instances in the GCP Marketplace. Google’s flexible approach to attaching GPU dies to standard CPU-based instance types means you can dial up or down the necessary GPU capacity for your instances depending on the size of your datasets and your compute needs.
We’re confident that MapD’s availability on GCP marketplace will further accelerate the adoption of GPUs as a key part of enterprise analytics workloads, in addition to their obvious applicability to AI, graphics and general purpose computing. Click here to try out MapD on GCP.