Home data

Why Blockchains Are a Peculiar Paradox for Data Management

Why Blockchains Are a Peculiar Paradox for Data Management

Bitcoin recently turned 13 years old, and over that time, the Bitcoin blockchain has remained uncorrupted and impervious to attack. As a result, the Bitcoin network maintains a pristine, permanent record of every single Bitcoin transaction that’s taken place. 

We live in a data economy, where data governance and data management are becoming some of the biggest challenges in the tech industry. So the very fact alone that Bitcoin has managed to demonstrate this unique ability to rigidly govern its data is impressive. 

However, there’s a peculiar paradox too. While blockchains may perhaps be the best-known way to ensure complete data governance, blockchains simply aren’t built to handle much data. Bitcoin generates about a gigabyte of data each day – a drop in the ocean compared to the 2.5 quintillion bytes of data created in the world daily.

It’s worth noting that this problem isn’t related to the often-discussed scalability problem. Even the fastest blockchains simply aren’t designed to handle vast volumes of data and storage. The fact that every piece of data needs to be verified by the network creates an inherent limitation. 

But there’s also the fact that blockchains are deterministic environments. Every piece of data must be verifiable, meaning that blockchains don’t handle any old data. They only handle the data within the environment of the blockchain itself - so in Bitcoin, only Bitcoin transactions. Smart contract platforms like Ethereum are more flexible, but smart contracts must conform to certain protocols to operate in the blockchain environment. 

These fundamental limitations are why blockchain often comes in for criticism, such as being a “solution in search of a problem.” In fact, over recent years, many blockchain developers have built solutions designed to overcome these inherent limitations, levelling up the capabilities of blockchain technologies. 


Data and File Storage

Many users may not realise it, but most blockchain applications aren’t quite as decentralized as they may seem. While the value transactions involving tokens are stored on a blockchain, all other data, including login credentials or identifying information, is most often stored on centralized servers from companies like AWS. 

Data and file storage protocols showed significant early promise in the blockchain space, and many have gone on to deliver working Mainnet’s that offer app developers the chance to rectify this issue. Filecoin is perhaps the best-known example, providing decentralized file storage for power users, including Wikipedia and now, New York City too. City officials are testing the decentralized protocol for storing data on demographics, air quality, and legal notices. 



The deterministic nature of a blockchain environment makes it challenging to bring in outside data sources because most of them are centralized, leading to challenges with trust. For example, a DEX requires price data to operate effectively, which is information held off-chain. The DEX could use a price feed API from a centralized exchange. But that opens the DEX up to all the risks of working with a centralized operator. If markets on the exchange are being manipulated, it will affect prices on the DEX. 


Decentralized oracles exist to overcome this challenge and provide a way for blockchain apps to operate using data that doesn’t exist within the blockchain environment. Chainlink is one such example, providing services such as decentralized price feeds and provably random NFT and number creation. 


AI Platforms

If something as straightforward as price data can provide the catalyst for an entire DeFi ecosystem, then imagine what bringing AI into the equation could achieve. That’s the vision of Oraichain, a blockchain protocol at the convergence of AI and blockchain. It allows blockchain developers to incorporate machine learning functionality into smart contracts, enabling a vast array of new features that wouldn’t otherwise be possible. 

For instance, in DeFi, AI models could be trained to carry out automated trading strategies across DEXs and decentralized lending protocols, minimizing human errors while profiting from the inflated yields. AI could also be integrated into authentication protocols, using advanced recognition methods to bypass the complexity of long strings of addresses and risks of lost passwords. 



To handle the vast amounts of data involved, Oraichain has released a Data Hub that’s used to organize, preprocess and standardize data for training and testing purposes. AI providers can create data lakes and data warehouses for use in on-chain and off-chain applications. The Data Hub is integrated with a Labeling Hub that annotates data and evaluates its integrity and trustworthiness. 

As blockchain developers become more innovative in overcoming the limitations of the technology, we can expect to see blockchain playing a bigger role in solving the challenges around data governance and data management. 

Disclaimer: This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.