Polygon: Web3's MongoDB and More

I first heard of Polygon in mid-2021. Friends of mine who were web3 entrepreneurs and NFT artists mentioned it as a promising project, providing a solid scaling solution for Ethereum. After some initial research, I learned that the founding team members were mostly from India, which immediately piqued my interest. I’ve been watching and researching Polygon ever since.

Last week, Stripe made a big announcement by adding crypto support in USDC (a stablecoin pegged to USD) for its global payout product, partnering initially with Twitter and deploying on, you guessed it, the Polygon network! This is not only a major validation for polygon, but also a testament to the potential and progress of the web3 ecosystem in India. As I expounded in my first post of 2022, in an age of technology abundance enabled by open source and web3 innovation, developer-turn-entrepreneurs can (and do) come from anywhere.

There is no shortage of content on the Internet about Polygon’s token price, fundraising, transaction volume, and traction in the developer community (more than 10,000 decentralized apps are being built on Polygon to date). However, the project warrants a comprehensive profile of its origin story, core technology, and potential as an investment opportunity.

That's what this post will attempt to do.

Origin Story

The founding story of Polygon began in a co-working space in Mumbai, India. It was pure serendipity and “love at first sight”.

Jaynti Kanani, a scrappy developer and early Bitcoin adopter, was hacking on an Ethereum scaling solution in 2017. Anurag Arjun, also a Bitcoin enthusiast, happened to be sitting right across from him at the same co-working space. Jaynti started talking to Anurag about what he was building (called Matic at the time) and asked Anurag to join him as a co-founder. Anurag said yes.

Soon after that, Jaynti met Sandeep Nailwal via a local crypto trading community. (Back then, most of the crypto communities in India were all about trading and making money, not building technologies or products.) Jaynti and Sandeep hit it off, and a 3rd co-founder of Polygon was “born”. Jaynti fondly recounted Polygon’s serendipitous founding story in this interview:

Mihailo Bjelic, the 4th co-founder and a Serbian entrepreneur, did not join Polygon until a couple of years later. Mihailo was working on a similar Ethereum scaling solution. Instead of continuing solo, he joined forces with the trio from India. Jaynti, Sandeep, and Mihailo all do a good amount of interviews and public presentations. Anurag is the most private one of all the co-founders. Sandeep and Mihailo now often appear together to talk about the latest news from Polygon or the ever-changing web3 space on crypto podcasts like Bankless. They are also the two co-founders most quoted in the media.

The co-founding team used to have C-suite titles like a traditional company: Jaynti was the CEO, Sandeep was the COO, etc. In late 2021, the team decided to do away with all these official titles, because the project is fully decentralized and having such C-suite titles would be anathema to that decentralized ethos. In other words, the co-founders want to “walk the walk’ as much as possible when it comes to decentralization.

Polygon counts famed investor Mark Cuban as an early backer. In February 2022, it announced a massive $450 million fundraising round, done via a private token sale. The round was led by Sequoia Capital’s India arm, with participation from the who’s who of crypto venture capital – Softbank, Tiger, Accel, Union Square Ventures, Digital Currency Group, Alameda Research, Dragonfly, etc. According to Sandeep, this fundraise should give Polygon another “three to five years of runway”.

Technology (By Analogy)

I like to understand technology by analogy, so I’ll apply that lens to explain Polygon without web3 jargon (e.g. L1, L2, etc.). There is a great analogous technology that is older, better understood, and applicable to almost every blockchain technology: databases.

At its core, a public blockchain is a distributed database that is not controlled by any single entity, thus decentralized. (A private blockchain, of course, is controlled by a private entity, and thus not decentralized.)

Ethereum is a decentralized, distributed database. Polygon, as an Ethereum scaling solution, is also a decentralized, distributed database. To achieve more scale with lower cost on top of Ethereum, Polygon makes certain technical tradeoffs. What kind of tradeoffs? A classic distributed database tradeoff, which Jaynti revealed in this interview.

In the interview, Jaynti was asked about what tradeoffs Polygon made between Consistency and Availability, according to the CAP Theorem. His answer was:

“Polygon chooses availability and gets eventual consistency in the current PoS network same as Ethereum. We made a design choice to replicate the same behavior as Ethereum consensus and reduce our engineering efforts at the beginning. And of course, it’s easy to implement :)” [emphasis mine]

You don’t have to know what the CAP Theorem is (an often-debated theoretical framework in database design) to understand the tradeoffs Polygon made. By prioritizing “availability” and settling for “eventual” consistency, Polygon is optimized to be fast and always on, always accessible, and never down. (To power use cases like payment, gaming, and decentralized finance, downtime is a big no-no.)

What gets traded off is the guarantee of data consistency, thus “eventual consistency”. (Think of “consistency” as accuracy at any given moment.) This is a similar and common design choice made by a generation of popular NoSQL distributed databases, like MongoDB, Cassandra, AWS’s DynamoDB, and Azure’s CosmosDB. (For more on MongoDB, I wrote a deeper profile on the company in December 2020.)

The “easy to implement” (with a smiley face) part of Jaynti’s answer is also worth unpacking. The surest way to keep a distributed database “available” and always-on is to add more replicas (or copies) of the same data. If the machine that stores one data replica goes down, just route the application’s traffic to another replica, and another replica, so the entire system is always “available” for that application. Adding new replicas (or “producing more blocks'' in blockchain parlance) is relatively easy (and fast to do), compared to keeping all the replicas consistent, which is quite hard and gets harder the more replicas you add. Polygon can live with these tradeoffs, because it sits on top of a slower but more consistent and more secure distributed database, called Ethereum.

With this technical understanding of Polygon’s characteristics in mind, Stripe’s choice of Polygon makes total sense.

Stripe has a long history and lots of experience using this type of distributed databases, specifically MongoDB. According to a case study published back in 2012, one of the reasons why Stripe engineers liked MongoDB was because getting new replicas set up and running was “incredibly easy”. Even today, Stripe’s job posting explicitly looks for engineers with experience in MongoDB, because its real-time database infrastructure is based on MongoDB – a massive distributed database system that has “strict requirements for security, durability, availability, latency, and scalability.” Sounds familiar?

Polygon is web3’s MongoDB, and more.

Web3’s MongoDB (and More)

Most investors don’t have a good framework to compare and analogize crypto projects to the more traditional investment universe. Bitcoin to gold is the closest thing we have. But if you grasp the technical tradeoffs made by different crypto projects, it is not hard to find analogous products in the more mature (and still growing) database industry.

If Polygon is web3’s MongoDB at the minimum, we now have an adequate comparison to assess Polygon’s future potential as an investment.

At MongoDB’s all-time high, achieved in November 2021, it reached a market cap of $42 billion. At Polygon’s all-time high, achieved on Christmas Day 2021, it reached a market cap of $20 billion. At the moment of this writing (April 23, 2022, Saturday afternoon Pacific Time), MongoDB has a market cap of $27 billion, while Polygon is trading somewhere between $10.5 to $11 billion (crypto never sleeps). To put this comparison in perspective, MongoDB was founded in 2007; Polygon was founded 10 years later in 2017.

Conservatively, Polygon’s market cap can grow 2x to 3x, just to match MongoDB’s market cap.

However, Polygon’s ambition appears much larger than MongoDB’s. It is betting aggressively on zero-knowledge (zk) proofs to increase its network’s scalability by committing $1 billion worth of Matic tokens to partnering or acquiring solutions in the zk space. It has already spent $250 million to buy Hermez and $400 million to acquire Mir. By comparison MongoDB’s three acquisitions to date, totaling a little over $100 million, look like pittance.

Polygon might just be the faster horse, and MongoDB is already pretty fast.

Just like how Polygon used to have a different name, Matic, MongoDB also used to have a different name, 10gen. When 10gen pivoted to focus on its distributed database product, the team chose the word “mongo”, which is a slang that means “huge” or “extremely” – perhaps to describe the amount of data such a database can scale to, perhaps to project the ambition of the company, or both.

If web3 is as big and as early as many developers and entrepreneurs believe, Polygon could be bigger than “huge”, bigger than MongoDB.

Disclosure: I hold some $Matic tokens.