These Mesmerizing Time-Lapse Maps Show How VC Money Is Changing Major Cities

San Francisco is being flooded with startup funding. Rents are sky high, newly-formed companies are offering lavish perks, and storefronts across the city are transforming.

Zillabyte software engineer Nikhil Karnik decided to analyze exactly how this growth has changed the city, as well as several other startup hotbeds such as New York and Austin, in a series of interactive maps.

Using Zillabyte, a framework for high-end data analysis, and the Crunchbase API, he created time-lapse visualizations of venture funding rounds for each city. The results are captivating.

Bubble sizes correspond to the total amount of funding raised, and the sample size for each city is limited to 1000 companies. Here's San Francisco:

It's clear that San Francisco has been flooded with venture capital, but Karnik's maps show exactly where the big venture-funded startups are taking root.

For instance, you can see why rent in SOMA - the upper-right hand corner of the map - is so expensive.

Next, check out New York:

Karnik's timelapse of funding rounds in New York City is limited to Manhattan, but you can see that startup growth since 2009 has been relatively steady compared to San Francisco's relative explosion.

Startups seem to prefer hip downtown neighborhoods such as SoHo or the Flatiron, as opposed to more traditional midtown.

Finally, let's take a look at Austin:

Austin's growth appears to be scattered across city limits, though many startups do line major roads and freeways.

Karnik notes that his methodology isn't perfect. Cities have very different histories and social dynamics that can either foster or stifle entrepreneurship, and he would like to look at population growth and development versus the rate of venture funding to gain further insights.

He's curious how much changing demographics in large urban areas correlate with the latest tech boom and if it's possible to pinpoint "up and coming" startup hubs using this type of analysis.

In the meantime, for more maps and a technical explanation of his methodology, check out Karnik's full blog post.