Bitgreen vs Algorand Scalability
Real-time TPS
Bitgreen has no data, while Algorand TPS is 5.07 tx/s
Max TPS (100 blocks)
Bitgreen has no data, while Algorand max TPS is 5,716 tx/s
Max Theoretical TPS
Bitgreen has no data, while Algorand max theoretical TPS is 9,384 tx/s
Transaction Volume
Bitgreen has no data, while Algorand transaction volume is 18,267 txns
Block Time
Bitgreen has no data, while Algorand block time is 2.81s
Finality
Bitgreen has no data, while Algorand finality is 0s
Type
Bitgreen has no data, while Algorand is a layer 1 blockchain
Launch Date
Bitgreen has no data, while Algorand was launched on Jun 12, 2019
Bitgreen vs Algorand Decentralization New
Nakamoto Coefficient
Bitgreen has no data, while Algorand Nakamoto Coefficient is 12
Validators/Miners
Bitgreen has no data, while Algorand has 1,903 validators
Stake/Hashrate
Bitgreen has no data, while Algorand stake is $481.1M
Consensus Mechanism
Bitgreen has no data, while Algorand is Pure Proof of Stake
Governance
Bitgreen has no data, while Algorand governance is on-chain
Other Comparisons
Bitgreen Comparisons
About Blockchains
About Bitgreen
Bitgreen is built on the Base network, a secure, low-cost, and developer-friendly Layer 2 blockchain (a scaling solution built on top of Ethereum) created by Coinbase. This integration provides Bitgreen with enhanced scalability, faster transaction speeds, and seamless accessibility for users.
Base's robust infrastructure ensures a reliable and efficient environment for the Bitgreen ecosystem, allowing us to focus on developing innovative applications and delivering real-world value.
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.