opBNB vs Algorand Scalability
Real-time TPS
opBNB TPS is 6.81X higher than Algorand TPS
Max TPS (100 blocks)
opBNB max TPS is 90.41% lower than Algorand max TPS
Max Theoretical TPS
opBNB max theoretical TPS is 49.25% lower than Algorand max theoretical TPS
Transaction Volume
opBNB transaction volume is 6.81X higher than Algorand transaction volume
Block Time
opBNB block time is 82.03% shorter than Algorand block time
Finality
opBNB finality is 100% longer than Algorand finality
Type
opBNB is a layer 2 blockchain, while Algorand is a layer 1 blockchain
Launch Date
opBNB was launched 4 years after Algorand
opBNB vs Algorand Decentralization New
Nakamoto Coefficient
opBNB Nakamoto Coefficient is 91.66% lower than Algorand Nakamoto Coefficient
Validators
opBNB has 99.94% fewer validators than Algorand
Stake
opBNB has no data, while Algorand stake is $481.1M
Consensus Mechanism
opBNB is Rollup (Optimistic), while Algorand is Pure Proof of Stake
Governance
opBNB off-chain governance is worse than Algorand on-chain governance
opBNB vs Algorand Real-Time TPS Chart
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Other Comparisons
opBNB Comparisons
About Blockchains
About opBNB
opBNB is an optimistic rollup network designed to enhance the scalability of the Binance Smart Chain (BSC). It aims to take the workload away from the mainnet and improve network performance. The opBNB network employs a unique approach to ensure transaction integrity and security. It leverages the main network (BSC) for final transaction validation on its execution layer, facilitated by a verifier mechanism, striving to achieve high throughput while maintaining security.
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.