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- Somnia Testnet vs Algorand
Somnia Testnet vs Algorand Scalability
Real-time TPS
Somnia Testnet TPS is 4.04X higher than Algorand TPS
Max TPS (100 blocks)
Somnia Testnet max TPS is 11X higher than Algorand max TPS
Max Theoretical TPS
Somnia Testnet max theoretical TPS is 112X higher than Algorand max theoretical TPS
Transaction Volume
Somnia Testnet transaction volume is 4.04X higher than Algorand transaction volume
Block Time
Somnia Testnet block time is 96.42% shorter than Algorand block time
Finality
Somnia Testnet finality is the same as Algorand finality
Type
Somnia Testnet and Algorand are both layer 1 blockchains
Launch Date
Somnia Testnet was launched 6 years after Algorand
Somnia Testnet vs Algorand Decentralization New
Nakamoto Coefficient
Somnia Testnet has no data, while Algorand Nakamoto Coefficient is 12
Validators
Somnia Testnet has no data, while Algorand has 1,903 validators
Stake
Somnia Testnet has no data, while Algorand stake is $481.1M
Consensus Mechanism
Somnia Testnet is PoS, while Algorand is Pure Proof of Stake
Governance
Somnia Testnet council governance is worse than Algorand on-chain governance
Somnia Testnet vs Algorand Real-Time TPS Chart
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Other Comparisons
Somnia Testnet Comparisons
About Blockchains
About Somnia Testnet
Somnia Testnet (Shannon) is the fastest and most efficient EVM Layer 1 blockchain ever, capable of processing over 1M+ transactions per second with sub-second finality. It is suitable for serving millions of users and building real-time mass-consumer applications like gaming, social applications, metaverses, NFTs, and more, all fully on-chain.
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.