Algorand vs Fogo
Algorand vs Fogo Scalability
Real-time TPS
Algorand TPS is 5.03 tx/s, while Fogo has no data
Max TPS (100 blocks)
Algorand max TPS is 5,716 tx/s, while Fogo has no data
Max Theoretical TPS
Algorand max theoretical TPS is 9,384 tx/s, while Fogo has no data
Transaction Volume
Algorand transaction volume is 18,104 txns, while Fogo has no data
Block Time
Algorand block time is 2.86s, while Fogo has no data
Finality
Algorand finality is 0s, while Fogo has no data
Type
Algorand is a layer 1 blockchain, while Fogo has no data
Launch Date
Algorand was launched on Jun 12, 2019, while the Fogo has no data
Algorand vs Fogo Decentralization
Nakamoto Coefficient
Algorand Nakamoto Coefficient is 12, while Fogo has no data
Validators/Miners
Algorand has 1,869 validators, while Fogo has no data
Stake/Hashrate
Algorand stake is $455.2M, while Fogo has no data
Consensus Mechanism
Algorand is Pure Proof of Stake, while Fogo has no data
Governance
Algorand governance is on-chain, while Fogo has no data
Algorand vs Fogo Developer Activity New
Developers
Algorand has 536 developers, while Fogo has no data
Repos
Algorand has 160 repos, while Fogo has no data
Commits
Algorand has 35,349 commits, while Fogo has no data
Stars
Algorand has 5,063 stars, while Fogo has no data
Watchers
Algorand has 980 watchers, while Fogo has no data
Other Comparisons
Algorand Comparisons
About Blockchains
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.
About Fogo
Fogo is an SVM chain running the Firedancer client in its purest form to achieve real-time experiences at scale.