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A quick introduction to blockchain scalability
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     Scalability is measured by how fast transactions process and how low the network latency is

Scalability is often associated with a single metric: TPS, or transactions per second. It is measured by how well the network handles a growing amount of transactions.

However, scalability encompasses much more than just TPS. It also covers how heavy blocks are (the data packet size), the network latency, and blockchain features like staking, sharding, and bridges to other blockchains.

Before I dive deep into how one could scale a blockchain – may that be through less security or less decentralisation – I will briefly explain how scalability is entangled with other key network features that always put an upper limit on how much any blockchain can scale.

Scalability, security, and decentralisation

When a crypto protocol aims at increasing scalability, either decentralisation, security, or both will be negatively impacted. 

When a crypto protocol targets lower scalability, security and/or decentralisation will increase. This is known as the scalability trilemma.

Whenever a cryptocurrency project claims they have “solved” scalability, make sure you look out for the downside:
  1. Is the project centralised? Some examples are Bitcoin Cash, EOS, NEO, and TRON. All these cryptocurrencies are able to scale in terms of how fast transactions process. However, all are much more centralised than Bitcoin or Ethereum.

  2. Is the blockchain less secure? When looking into security, one must always keep in mind there’s short-term and long-term security. Therefore, the question any investor or enthusiast should ask is the following: “If there’s a successful attack on the network, how can it be reversed”? If the answer is through a roll-back, minting/distributing more coins, or any other solution that involves changes to the supply or coin ownership, the project cannot be secure because the blockchain isn’t immutable.
If scalability has any serious impact on the supply or on the network’s capacity to process transactions, technical and economical issues arise. When the supply changes, value may be lost because investors lose confidence in the blockchain’s immutability. When nodes cannot process transactions because there’s just too many, or because the frequency of occurrence is too high, transactions may be lost. If value is lost, the network won’t be considered secure in the long term.

How to scale a blockchain

There are plenty of ways to scale cryptocurrencies. In this section, I will look into which methods are the most commonly used and why. I will also aim to explain how each solution achieves scalability by diminishing either decentralisation or security.

Staking/voting consensus

PoS, or Proof-of-Stake, requires participants to stake some of their tokens in order to become network validators. PoS is seen to have two main issues. The first is the ‘nothing at stake’ problem, where participants can’t lose their stake even if they voted for all blocks and did not follow the protocol rules. The second is the fact the network is prone to more centralisation as there is no mining. Both problems are addressed in current pure-PoS implementations, such as Ardor.

Delegated Byzantine Fault Tolerance (DBFT) is another method to scale a blockchain. It allows faster consensus through voting and is based on a federated consensus, meaning the network reaches consensus through the agreement of a number of central authority nodes. Although this consensus algorithm allows scalable solutions to be built on top, it decreases security and user privacy as the network is not truly decentralised and has central points of failure.

P2P channels

P2P means communications do not rely on any intermediary and consensus on the state of the network is reached through the use of rewards, incentives, and applied game theory.

The best example so far of P2P channels built on top of a cryptocurrency is the Lightning Network protocol.

The Lightning Network is a payments channel linked to the Bitcoin network, meaning there can be many different implementations of the same protocol by multiple companies. The Lightning Network (LN) refers to both Lightning Labs’ LN and Blockstream’s LN.

Instead of relying on hard forks to upgrade transaction storage per block (block weight), the LN allows for the integration of off-chain payment state channels between nodes. This means that instead of validating all information on the main chain, the LN creates direct off-chain connections between nodes, which are opened up by storing Bitcoin on that channel.

Nodes open routes among various chains so payments can hop between nodes until they reach their final destination.
With the Lightning Network, any user can set up a Lightning node and open channels with any node in the network. This has great advantages in terms of speed and cost, as fees would be much cheaper because only settlement transactions are validated on the Bitcoin blockchain.


The Statechains protocol, a side-chain protocol for Bitcoin, provides a simple alternative method for transferring funds between agents. This protocol only uses the layer-one blockchain when entering or exiting the system or when there are disputes – much like Lightning.

A Statechain is a ledger that contains the history of every UTXO (unspent transaction output) that is under its management. This ledger is also maintained by the Statechain entity and servers, making them accountable for misbehaviour.

To improve security, more than one entity can be added as a Statechain validator, meaning it’s possible to make a federated group of signatories like a multisig group.

Statechains also have a downside. The absolute need to transfer UTXOs in full as they cannot easily be split into smaller amounts means it’s difficult to micro-transact using Statechains.

When compared to the Lightning Network, Statechains offer more security as coins can be transferred directly without having to find a path on a network of sufficiently funded channels, which can be a problem for routing and security.
Examples of Statechain implementations include Rootstock and Loom.


Database sharding, most commonly known simply as sharding, is a technique that allows nodes to process only small parts of entire blockchain transactions. At the same time, it makes sure the state of the whole chain is correctly ordered and validated.

Sharding creates multiple smaller databases that only store local copies of transactions. Each database validates and stores a small part, making the system lighter as a whole.

There are two major versions of sharding currently being used.
  1. Partitioned sharding, where shards don’t communicate with each other directly through a central relay.

  2. State sharding, where shards communicate with each other through a state, or central, relay.
Ethereum 2.0 is implementing sharding, much like Polkadot and Ziliqa.

For more information on sharding, check out this guide.

by Pedro Febrero

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