Antonio Cotroneo
May 13, 2021

OmniSci Free is Now on the AWS and Azure Marketplaces

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Deploying enterprise software shouldn't be intimidating or inconvenient, but often bare metal server installs embody that discomfort. 

Either you have to upskill to become better versed in Linux server administration, or you don't have the time or energy to provision machines and track down the proper drivers.

Don't get me wrong. Traditional manual deployments still have their place in the IT landscape and offer robust, flexible options for experienced users to handle tricky governance rules.

But the growing desire for convenience, simplicity, and improved time-to-value has prompted accelerated growth in cloud marketplace offerings in recent years. 

Last year Forrester observed that 73% of B2B software customers found cloud marketplaces to be convenient, 68% felt they simplified acquisition, and 54% thought they provided faster access to tools.

Deploying OmniSci Free is no different. In this post, we'll review the OmniSci Free offerings on the AWS and Azure Marketplaces and show you how to get started with video tutorials that showcase deployments that take ten minutes or less!

What is OmniSci Free?

OmniSci Free is a full-featured OmniSci experience that includes the latest release of OmniSciDB, Render, Immerse, and the OmniSci Data Science toolkit, a complete set of Python-based tools deeply integrated with OmniSci and accessible directly from Immerse. 

Users can implement the OmniSci stack however they see fit, with up to 1GPU, 32GB memory capacity, and three active user sessions, suitable for datasets with 100s of millions of rows. Sign up here to receive a license and apply it to the following marketplace listings.


OmniSci Free on the AWS Marketplace

The AWS Marketplace is an incredible resource that lists software products from independent companies, like OmniSci, making it easy to find, test, buy, and deploy solutions that run on AWS.

OmniSci maintains a handful of AWS listings for different applications, including OmniSci BYOL (Free and Enterprise) and OmniSci Enterprise Edition (AWS Hourly).

Those needing to launch a fully-featured, GPU-enabled version of OmniSci Free should use the OmniSci BYOL (Free and Enterprise) Amazon Machine Image (AMI). Watch the video above to learn how to launch an AMI in just a few minutes. 

Amazon EC2 G4 single GPU machines are the recommended and default option for OmniSci Free deployments. G4 instances are cost-effective and versatile GPU instances for deploying analytic and graphic-intensive applications like OmniSci.

The OmniSci BYOL (Free and Enterprise) AMI provisions the following standard configuration and costs approximately $1.204/hr: 

  • g4dn.4xlarge instance
  • 16 vCPUs
  • 64 GiB memory
  • 225 GB of EBS and local NVMe SSD storage
  • 1 NVIDIA T4 GPU
  • 16 GB GPU memory

p2.xlarge and p3.2xlarge are other common EC2 instances used for OmniSci Free. Be cautious, though. The p2 instances use k80 GPUs, which were first released in 2014 and are starting to show their age, and while the p3 instances use v100s, they cost nearly three times as much as the base G4dn instances.


OmniSci Free on the Azure Marketplace


Like the AWS Marketplace, the Azure Marketplace has a wide variety of certified applications and services that organizations can seamlessly deploy onto optimized Azure configurations.

The OmniSci Enterprise & Free Edition BYOL Azure Virtual Machine (VM) listing is the choice for feature-complete deployments of OmniSci Free on the Azure Marketplace. Watch the video above to learn how to create a VM in a matter of minutes. 

NCv3-series VMs, powered by NVIDIA Tesla v100 GPUs and Intel Xeon E5-2690 v4 (Broadwell) CPUs, are the standard machine type for OmniSci Free. These VMs deliver high-performance, low-latency computing designed for visualization-intensive workloads like Immerse.

The OmniSci Enterprise & Free Edition BYOL Azure VM reserves the following configuration by default and costs approximately $3 to $4 an hour:

  • Standard_NC6s_v3 VM
  • 6 vCPUs
  • 112 GiB memory
  • 736 GiB of SSD storage
  • 1 v100 GPU
  • 16 GiB of GPU memory

Standard_NC12, Standard_NC6s_v2, Standard_NC16as_T4_v3, and Standard_ND6s are other well-known Azure VMs used for OmniSci Free. If there are still questions about what hardware to use, refer to the OmniSci Hardware Reference page and remember that Free limits users to 1GPU and 32GB memory capacity.

Deploy an OmniSci Free instance of your own from the cloud marketplace of your choice with ease and confidence!


As demonstrated, AWS and Azure marketplace images are an excellent way to get up and running with OmniSci Free and reduce the time to value. 

Each of these offerings advances our goal of making analytics instant, powerful, and effortless for everyone. Shortly we will be adding OmniSci Free images to Google Cloud Platform (GCP) and other providers.

If you decide to deploy an instance through a cloud marketplace, please share your experience with us on LinkedInTwitter, or our Community Forums!



Antonio Cotroneo is the Director of Technical Content Strategy at OmniSci. He has spent his career helping people around the world maximize their geospatial data, mapping technology, and spatial analyses to make critical decisions for their customers and community. Antonio has a M.S. from the University of Southern California in Geographic Information Science and Technology and worked as Esri for over 5 years. He currently lives in Charlotte, NC with his wife and two children.