Mazze vs Algorand
Mazze vs Algorand Scalability
Real-time TPS
Mazze has no data, while Algorand TPS is 5.24 tx/s
Max TPS (100 blocks)
Mazze has no data, while Algorand max TPS is 5,716 tx/s
Max Theoretical TPS
Mazze has no data, while Algorand max theoretical TPS is 9,384 tx/s
Transaction Volume
Mazze has no data, while Algorand transaction volume is 18,848 txns
Block Time
Mazze has no data, while Algorand block time is 2.77s
Finality
Mazze has no data, while Algorand finality is 0s
Type
Mazze has no data, while Algorand is a layer 1 blockchain
Launch Date
Mazze has no data, while Algorand was launched on Jun 12, 2019
Mazze vs Algorand Decentralization
Nakamoto Coefficient
Mazze has no data, while Algorand Nakamoto Coefficient is 12
Validators/Miners
Mazze has no data, while Algorand has 1,862 validators
Stake/Hashrate
Mazze has no data, while Algorand stake is $449.4M
Consensus Mechanism
Mazze has no data, while Algorand is Pure Proof of Stake
Governance
Mazze has no data, while Algorand governance is on-chain
Mazze vs Algorand Developer Activity New
Developers
Mazze has no data, while Algorand has 536 developers
Repos
Mazze has no data, while Algorand has 160 repos
Commits
Mazze has no data, while Algorand has 35,295 commits
Stars
Mazze has no data, while Algorand has 5,061 stars
Watchers
Mazze has no data, while Algorand has 981 watchers
Other Comparisons
Mazze Comparisons
About Blockchains
About Mazze
Mazze is a Layer 1 blockchain that redefines performance through its PoW-based DAG architecture. Experience EVM compatible smart contracts and unparalleled privacy with ZK proofs.
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.