FREE Preview

HEAVY.AI for Mac

Analytics at the speed of curiosity


HEAVY.AI Data Science Installer

We've partnered with Quansight to package an all python-based tooling into a self-contained installer package for the Mac.  This installer is compatible with the most recent version of HEAVY.AI for Mac. Learn more about the new addition here.
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I’ve never seen an analytics platform on a personal laptop process a billion rows so performantly before. Nothing else comes close. [HEAVY.AI] running on a MacBook Pro opens up an entirely new world of data exploration, interactivity, and scale for a much larger audience.

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Mark Litwintschik
Technical Blogger


Query 1B+ rows

Fast AF

>5B rows per sec


Visual interactivity

Instant. Powerful. Effortless.

In this preview, analyze hundreds of millions of data points with your personal Mac.

  • Visual analytics at scale
  • Data science integration
  • Interactive SQL editor
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Frequently Asked Questions

Where can I ask questions or post feedback?

Find a link in the Help section of HEAVY.AI for Mac to say virtual 👋🏽. Alternatively you can reach out to us at where our minions await. Finally, our community is a great place to dive deep and interact with a community of 🤓 like you.

Is it just an experiment? Are you going to make a product out of this?

That's a secret, but we can tell you that in ⬛⬛⬛⬛⬛ we plan to ⬛⬛⬛⬛⬛ on a ⬛⬛⬛⬛⬛ which should feature ⬛⬛⬛⬛⬛ and provide groundbreaking new ⬛⬛⬛⬛⬛ and ⬛⬛⬛⬛⬛ and at even larger scale. We can't wait!

Where do I learn how to use this?

You can go to our Immerse documentation to learn more, or chat with us under Help. We’re also going to have a series of videos soon on our YouTube channel. Be sure to like, subscribe, and click that notification bell.

I tried to do X, and it didn't work, or crashed!

Sorry about this! This is a ‘use at your own risk’ experimental build of OmniSci for Mac. We squashed a lot of bugs to get here, but it is honestly still alpha quality at this time. Bugs aside, it is worth remembering that you can do a lot of things in SQL that are, despite our best intentions, just bad - e.g. running a multi-way self-join on a 100 million row table, or a ‘select *’ query with no limit on a billion row table from SQL editor. The good news is, your feedback and our constant focus on bug bashing will help to make this better! 

What else can I do besides create dashboards?

Try to take over the world. Under the hood is the exact same HeavyDB that is among the fastest analytical databases in the world. You can access it also via the included SQL Editor. Over the next few weeks, we’ll also show you how to use HEAVY.AI in a Data Science workflow with JupyterLab. Plus, Immerse itself has lots of powerful features such as crossfilter and cohort analytics.

I have Tableau/Qlik/Spotfire. What does this give me that they don't?

A full fledged analytical SQL engine (HeavyDB) that is run in production by our largest customers, offering millisecond latencies on billion row datasets. An advanced data visualization solution which you can use to build dashboards over 100 million row datasets on your laptop. Deep data science integration with the PyData stack. All for the price of - $0, for now.

What kind of Mac should I run this on?

Any Intel Mac (MacBook Pro, iMac or Mac mini) should work, but we recommend more modern machines with these specs:Recommended: 7th generation Intel processor with 4+ cores and 16GB of RAM. Ideal: 32GB of RAM or higher for datasets with 100-250 million rows2019/2020 16” MBP with 64GB easily handles larger datasets up to a billion rows (that’s what Mark ran the taxi rides query benchmark on).OS: macOS Catalina(10.15). If you are on 10.14, try to right click on the file and click on open. For other issues, review this page:

With Apple moving to ARM, will this be a short-lived experiment?

We got ourselves a developer transition kit. We’ll keep you posted!

What about Windows laptops? Linux? Docker?

Windows folks - sorry you can’t run HEAVY.AI on your epic gaming platforms...yet. However, you can already run HEAVY.AI (including Nvidia GPU support) on Linux and Docker. In fact you can run HEAVY.AI on your Mac (or Windows) with Docker, but you’ll pay a performance cost due to virtualization.

Why don’t I get the cool geo charts I see on your demos?

While we actually have work in flight to render on GPUs we are not running compute on (i.e. the AMD and Intel GPUs present on a modern Mac), rendering on a Mac is trickier than Linux or Windows due to the lack of modern OpenGL support. There are lots of ways you can build scalable geoviz outside this though, using our Python tools, and we are looking at ways of supporting scalable frontend rendering for the Mac offering. Again, if you’re interested, let us know.

Don't be latent...

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