Welcome back to MondayMunday, my blog on all things fintech and crypto. I’d be remiss not to have a note on ‘The Merge’, the ability to transfer a live running ledger to a new consensus mechanism without any major hiccups is an impressive feat in its self and should be applauded. Furthermore, the transition to PoS removes large amounts of criticism around energy consumptions of Ethereum and its ability to be a backbone of a new financial system. Major wins in the viability of blockchains to compliment traditional financial infrastructure! However, today we are going to do something different, I have always wanted to speak to upcoming founders about their products and break them down. Today I had such an opportunity and I am excited to share it with you! If you know any other founders I should speak to feel free to reach out, i’d love to chat… Now to the post.
Today we are kicking off The Intersection, a series where I chat with fintech/blockchain founders to uncover what they are working on and why they are important to bridging crypto and traditional finance.
Last week I was fortunate to have a 30-minute chat with Mike Ritchie (eternally grateful) about his new project Luabase. I am excited to share my learnings in public on new companies and founders.
What is Luabase?
Luabase is building the core components of the Modern Data Stack (MDS) for Web 3. They are abstracting away the complexities of managing a data pipeline for turning raw blockchain data into pipelines that can be analysed using SQL, the primary tool of data analysts/scientists.
A quick overview of the Modern Data Stack
Before we dive into how Luabase is building the MDS for Web3, let's align on what it is and how it allows companies to become data-led.
The modern data stack refers to a set of cloud-native tooling that is put together to allow organizations to transform data for analysis and product integrations.
Prior to the revolutions in the cloud, we saw teams store data in warehouses on-premise. Due to the nature of computing power required and engineers managing and processing data, the ability to leverage data to make business and product decisions were reserved for the largest companies.
The advent of cloud computing allowed the cost of storing, accessing, and computing on these data sets to draw insights. This started with Amazon Redshift which launched cloud-based data processing, which gives you the ability to scale compute and storage independently as needed to meet changing workloads.
This has led to a new way to process data using cloud-based services to extract, transform and load data from data sources to be used for analytics purposes. This process is commonly known as ETL.
Extracting refers to taking data from original sources data sources (i.e. application data or SaaS tool data such as sales revenues)
Transforming refers to formatting, and combining data so this ‘clean’ data can be easily analysed.
Loading refers to storing that ‘clean’ data to be used in your product as insights or plugged into visualization tools.
Whilst we have referred to the process as ETL, oftentimes ELT occurs, where data is extracted and loaded in a firms databases and systems, subsequently, it can be transformed for a variety of uses such as data visualization and product insights.
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This modern stack for managing data has allowed companies to implement data-driven processes in their business with ease.
TL;DR - The nature of the MDS has abstracted away the complexity and cost of managing and manipulating customer and product information for business, data analytics is now accessible for all firms to execute.
Note: this is a whistle-stop tour of the MDS, and there is a lot more nuance and detail.
The typical data journey for blockchain start-up with data?
We are seeing this problem on day one with blockchain start-up, the ability to query the blockchain is essential when building products, you made need to check on the success of a transaction or execution of a smart contract for example. To do this currently a start-up would need to run or rent nodes from infrastructure providers to have access to the ledger. From here, they would have to build their own MDS to ingest the blockchain data and load and transform it to build SQL queryable data pipeline. This would be a very costly and time-consuming task requiring heavy infrastructure building and engineering to be done.
This is the problem Luabase are solving… they allow existing data engineers to leverage known processes to analyse blockchain data without worrying about infrastructure.
History of Luabase
Mike had previously worked at Bank of America as SVP of Analytics and went on to found SeekWell, a reverse ETL platform (reverse ETL means taking data to enrich existing SaaS infrastructure e.g. taking stored customer insights and using it to enrich your Salesforce data). Mike has firsthand seen the problems relating to data for finance teams, furthermore, he has helped build a key component of the MDS during his time SeekWell. A penchant for solving and abstracting complex data problems has been Mike’s strong suit in his career.
Mike was also one of the early joiners in the Bitcoin and Ethereum subreddits, he originally had ideas to build bitcoin arbitrage bots and ways to detect Tornando Cash interactions. These ideas, whilst pique interest, are worthwhile the pursue if the cost of creation is too high.
Herein, is the true problem, execution of these ideas given the current data stack in Web3 is extremely difficult. Whilst, by nature Web3, is open, that doesn’t mean core services exist to make it developer friendly. Data is one such case, open access to blockchain data doesn’t make it easily useable for regular data practitioners.
This is why Luabase was born!
The Product
Luabase ingests blockchain data and transforms it into SQL queryable datasets. Users can also enrich this data by adding custom data sources. This allows users to combine on-chain with off-chain data with on-chain data. They can then export these data pipelines as APIs to use in their product.
Looking at our MDS stack, Luabase abstracts the complexity of extracting and loading blockchain data, and provides initial data transformation to make data SQL queryable.
Use-cases
Given the power of this tool to make blockchain data accessible to any SQL practitioner, the initial use-case has come from trading firms who want to use blockchain data to make investment decisions and web3 product teams who want to focus on product building and less so on building data pipelines for product analytics.
An example is ThirdWeb, they are a developer platform that makes blockchain development simpler through smart contract SDKs. In their product, they wanted a reporting function, so when users implemented SDK they could get status on their smart contract. Using Luabase they could create SQL queries to check this for users and connect it to their product using an API, this saves considerable development time.
Key Lessons for Web3 x Fintech builders
Scalability vs Decentralisation
Web3 is open and decentralized by nature, however, to build robust systems you need scalable infrastructure. Deciding the level of decentralization your customers need for your solution can help you when building. In the case of Luabase, they are providing a service over open data, decentralisation of the service provider is the trade-off for a user-friendly way to abstract away the complexities of infrastructure.
How to sell Web2 products in Web3
Luabase is akin to traditional developer software sales cycles, however, crypto projects also have many hobbyists who also want to experiment with the platform. Given this, you need a way to scalably serve new builders to gain adoption, whilst finding ways to target enterprise sales to generate revenue. So far Luabase has managed the trade-off well with a product-led approach to platform discovery (you can easily sign up and use the platform from their website) and initial enterprise design partners to help them discover and validate enterprise offerings.
Why this is important for the intersection?
We need to simplify the developer stack to onboard the next generation of builders
If we are to see the next generation of products being built on Web3, we will need builders who come from diverse backgrounds to help solve problems using this technology. Given this, we need platforms that provide Web2 tooling to Web3 platforms to aid the development of this nascent industry. Luabase achieves this by allowing data practitioners to leverage SQL to analyse blockchain data.
We need ways to combine Trad-fi and DeFi data
If we believe a world will exist where Trad-fi and DeFi merge, we need solutions that allow the mixing of data from these two worlds so practitioners can build new and wonderful products. Luabase achieves this by allowing users to mix their own data sets with on-chain data sets.
I am excited to see how companies lower the barrier for accessibility of blockchain data. As we have seen with with traditional fintech, data access has been crucial for building new business models and products (examples include Open Banking and alternative data for credit decisioning). The ability of blockchains to provide a common data layer make this an advancement for the types of financial products we can build. However, we need solutions like Luabase are essential for providing common tooling around data to enable builders to leverage the data at their disposal.
If you are fintech builder or investor feel free to reach me by replying to this email or DM on Twitter or LinkedIn, I’d love to chat! 🙏