TON vs Algorand Scalability
Real-time TPS
TON has no data, while Algorand TPS is 5.15 tx/s
Max TPS (100 blocks)
TON has no data, while Algorand max TPS is 5,716 tx/s
Max Theoretical TPS
TON has no data, while Algorand max theoretical TPS is 9,384 tx/s
Transaction Volume
TON has no data, while Algorand transaction volume is 18,524 txns
Block Time
TON has no data, while Algorand block time is 2.81s
Finality
TON has no data, while Algorand finality is 0s
Type
TON has no data, while Algorand is a layer 1 blockchain
Launch Date
TON has no data, while Algorand was launched on Jun 12, 2019
TON vs Algorand Decentralization New
Nakamoto Coefficient
TON has no data, while Algorand Nakamoto Coefficient is 12
Validators/Miners
TON has no data, while Algorand has 1,903 validators
Stake/Hashrate
TON has no data, while Algorand stake is $481.1M
Consensus Mechanism
TON has no data, while Algorand is Pure Proof of Stake
Governance
TON has no data, while Algorand governance is on-chain
Other Comparisons
TON Comparisons
About Blockchains
About TON
The Open Network (TON) is a decentralized and open internet platform made up of several components. These include: TON Blockchain, TON DNS, TON Storage, and TON Sites. TON Blockchain is the core protocol that connects TON’s underlying infrastructure together to form the greater TON Ecosystem. TON is focused on achieving widespread cross-chain interoperability, while operating in a highly scalable secure framework. TON is designed to process millions of transactions per second (TPS), with the goal of eventually reaching hundreds of millions of users moving forward.
About Algorand
Algorand emerges as a blockchain platform committed to fostering transparency and enabling the growth of decentralized projects and applications. Operating as a public, decentralized blockchain, it leverages a Pure Proof-of-Stake (PPoS) consensus mechanism to uphold network security, efficiency, and decentralization. Powered by the Algorand Consensus Algorithm, the network employs a combination of cryptographic techniques and random selection to attain consensus, effectively addressing the constraints of traditional consensus mechanisms.