Blockchain offers enterprises a great opportunity to provide services in a secure, transparent, and trustless environment. However, this usually comes with a challenge, as decentralization usually slows down a system as usage grows.
While central systems are easy to scale without issues, scaling decentralized systems often means reducing the number of players, which in turn affects security. As decentralized systems become more popular, enterprises have had to find a different way to ensure blockchain scalability.
In this guide, we’ll look at the various considerations that developers need to make to balance security and performance while avoiding bottlenecks as usage grows.
Understand the trade-offs
Decentralization is the main point behind blockchain’s appeal as a technology and ecosystem. When you have more nodes validating transactions and maintaining a ledger, the network becomes more secure and less prone to manipulation.
However, that decentralization increases latency. Each additional node that needs to verify transactions needs communication with the rest of the system for pretty much everything, which slows down transactions when usage is high.
On the other hand, a more centralized network can process networks fast without huge infrastructure costs. But since it’s more concentrated, the network players can collude to change transactions, or governments can intervene easily.
Use hybrid models strategically
A popular way to solve the trade-offs is to use a hybrid approach.
This generally involves viewing the operations as different layers, then taking the less sensitive ones to a different chain. In most cases, this is usually the transaction processing part, but some developers still export the data availability layer to another chain. Either way, you can easily scale while still leaving finality to a highly decentralized chain.
In practice, this means:
- Settlements and a few transactions are quite critical, so you leave them on the base chain. This means that the finality of a transaction is still sent back to a blockchain like Ethereum for confirmation.
- The actual transaction process moves from Ethereum to a different layer that can handle them faster.
- The transaction summaries still need to be pushed to the base layer to ensure integrity, so there’s an interactive layer.
This approach makes it easier for developers to scale, innovate, and adopt new technologies without bottlenecks.
Optimize consensus mechanisms
Every transaction that takes place on the blockchain needs to undergo consensus. However, there are different methods that determine how the transaction is validated, how quickly the confirmations occur, and how trust is maintained throughout the process.
Key considerations include:
- Selecting a consensus algorithm – There are many of these, including Proof-of-Stake (PoS), Proof-of-Work (PoW), and Practical Byzantine Fault Tolerance (pBFT). Match it to your use case.
- Adjust block size and frequency to fit your needs – When you make the blocks larger, you can process more transactions at the same time, but at the risk of latency. When the blocks are smaller, you’ll have faster confirmations, but you can also overload the network.
- Maximize your secondary layer – There are transactions that don’t need confirmation right away. Processing them here helps reduce congestion.
Note that these mechanisms keep evolving, so ensure you design the network in a way that the algorithm or its parameters can be updated.
Focus on modular and scalable design
When you’ve structured the architecture well, it will be easier to maintain both performance and scalability as the blockchain grows.
The best approach to this is to ensure that you can easily change most of your blockchain components. For example, you can separate critical functions like smart contracts, validation layers, and data-handling components. This way, you can easily scale some parts, make upgrades, or bring in new features without disrupting the entire system.
