Get HEAVY.AI Free
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What's Next?
1. Get OmniSci
2. Install / Configure OmniSci
3. Confirm License
Optimize your HEAVY.AI Experience
Yes!
The HEAVY.AI Free install is for Linux. Want to run HEAVY.AI on your Mac? Check out our Mac Preview.
Yes. HEAVY.AI Free can be launched in minutes on your favorite cloud platform with dedicated marketplace images. See Install Options for all available options.
HEAVY.AI Free supports up to 3 active user sessions at a given time, although you can create as many users as you want. Need more? Contact us to discuss our Enterprise License , or pay by the hour on AWS.
HEAVY.AI Free allows the usage of 1 GPU. Need more? Contact us to discuss our Enterprise License , or pay by the hour on AWS.
HEAVY.AI Free supports up to 32 GB of GPU memory and up to 32 GB of CPU memory. Need more? Contact us to discuss our Enterprise License , or pay by the hour on AWS.
A high-performance analytical SQL engine (HeavyDB) that runs in production at our largest customers, and offers millisecond query response times on multi-billion row datasets. A next-generation data visualization solution in HeavyImmerse, that you can use to build no-code dashboards over multi-billion row datasets, and includes advanced features like spatiotemporal cohort analytics and integration with the HEAVY.AI Rendering Engine to enable granular visualization of billions of geospatial features. Deep data science integration with the HEAVY.AI Data Science Toolkit, all out of the box. A thriving community of HEAVY.AI users and enthusiasts on our community forums. All for no charge.
While GPUs are not required to run HEAVY.AI, we really recommend GPU infrastructure for HEAVY.AI Free to get the most optimal and complete experience possible with HEAVY.AI today. You can start small though, with single GPU instances in the cloud, using our AWS marketplace images. If you're okay living without some of the key GPU-enabled HEAVY.AI features including our GPU-rendered geocharts, you can run HEAVY.AI quite well on your Mac with our Mac Preview, or on any CPU server or workstation with at least 8GB RAM.
Start by choosing the install package that works best with your setup and then follow our documentation.