The world of web3 data is vast and ever-growing, but it can be incredibly frustrating to access. With all the different blockchains, protocols, and tokens, navigating and understanding this complex data ecosystem requires an upfront investment of time, patience, and money. The data is raw, unindexed, and brutal to merge with third-party data sets. Dapp providers often find themselves building custom tools over leveraging open source and paid solutions.
The current attempts to address these issues are futile as they focus on treating the symptom instead of the disease.
The data accessibility problem in web3 is not a data problem, it’s an infrastructure problem.
Now that we’ve properly defined the problem, we can implement a strategy that leads to success.
Throughout the last two years, we used several web3 indexing products. Some, open-source, provided value in the short term. Over time the value was reversed through unannounced deprecated services and the additional resources we invested in making the product work. We later found centralized products that charge for their APIs. It was like having two versions of our town library next to each other. One makes you pay but gives you access to their card catalog. The other is free but requires a bit more time and creativity to find your book. After a few times navigating and getting comfortable in the free library, there is zero value in paying for admission next door. Like the soon-bankrupt library, companies charging for API access will soon reevaluate their business models.
As we transition into an ecosystem with free indexing APIs, there is an additional hurdle that needs to be addressed. Simplifying access to indexed data is great but not useful if it's not easily configurable into different forms. Please welcome, transformers.
Transformers transform the raw, indexed data into configurable forms. The result is a composable infrastructure that any individual, company, or government building in web3 can configure to their needs.
Looking at data from a single NFT project via an indexed API can give us insight into transaction data. Who is the largest holder? When did they buy? Where did they buy? Powerful, yes. However, scaling across thousands of transactions or adding web2 data into the model is hard. Transformers give builders the ability to overcome these challenges and provide valuable datasets to their users.
Leveraging this infrastructure, let's use the Ethereum, Tezos and Polygon NFT Indexers to get a few baseline stats. Next, we’ll configure the transformer to compare net new purchases from September 2022-December 2022 on Solona, Ethereum and Polygon using wallet addresses.
There are over 7.5 million wallets on Ethereum that have ever owned an NFT
The average NFT price in 2022 on Ethereum was $343
There are 45,000 ERC721 and 30,000 ERC1155 NFT contracts on Ethereum.
During 2022, Tezos NFT sales (XTZ) were up 115%
NFT Market place volume peaked at 1.7 billion on Ethereum in August 2021
NFT wash trading peaked in Jan 2022 on Ethereum with 4.1 billion in wash trades versus 1.1 billion in organic trading volume.
From Sept 2022-Dec 2022, new users buying NFTs on Solona dropped 63% and 36% on Ethereum. During that same time, new users buying NFTs on Polygon grew more than 500%.
With composable infrastructure, developers reduce superfluous costs and technical debt while providing more value to their users.
To realize Web3's goal of surpassing web2, the applications must be significantly superior to their web2 counterparts. Developers require the same, if not better, tools and infrastructure as those available in web2. With seven years of experience building custom data solutions and paying for what should be free, we’ve gone all in on solving web3’s datainfrastructure problem.