Solana vs Algorand Scalability
Real-time TPS
Solana TPS is 118X higher than Algorand TPS
Max TPS (100 blocks)
Solana max TPS is 17.61% lower than Algorand max TPS
Max Theoretical TPS
Solana max theoretical TPS is 6.93X higher than Algorand max theoretical TPS
Transaction Volume
Solana transaction volume is 118X higher than Algorand transaction volume
Block Time
Solana block time is 86.23% shorter than Algorand block time
Finality
Solana finality is 100% longer than Algorand finality
Type
Solana and Algorand are both layer 1 blockchains
Launch Date
Solana was launched 9 months after Algorand
Solana vs Algorand Decentralization New
Nakamoto Coefficient
Solana Nakamoto Coefficient is 1.75X higher than Algorand Nakamoto Coefficient
Validators
Solana has 45.34% fewer validators than Algorand
Stake
Solana stake is 152X higher than Algorand stake
Consensus Mechanism
Solana is PoS, while Algorand is Pure Proof of Stake
Governance
Solana off-chain governance is worse than Algorand on-chain governance
Solana vs Algorand Real-Time TPS Chart
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Other Comparisons
Solana Comparisons
About Blockchains
About Solana
Solana stands out as a high-performance blockchain, celebrated for its scalability, speed, and minimal transaction expenses. Featuring a distinctive consensus mechanism dubbed Proof of History (PoH), Solana achieves remarkable scalability and efficiency. Tailored to accommodate dApps, it excels in processing a vast number of transactions swiftly, thereby slashing processing durations and fees. These attributes make it a compelling platform for developers within the cryptocurrency realm.
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.