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- Zeitgeist vs Algorand
Zeitgeist vs Algorand Scalability
Real-time TPS
Zeitgeist TPS is 100% lower than Algorand TPS
Max TPS (100 blocks)
Zeitgeist max TPS is 99.99% lower than Algorand max TPS
Max Theoretical TPS
Zeitgeist max theoretical TPS is 84.01% lower than Algorand max theoretical TPS
Transaction Volume
Zeitgeist transaction volume is 100% lower than Algorand transaction volume
Block Time
Zeitgeist block time is 4.87X longer than Algorand block time
Finality
Zeitgeist finality is 100% longer than Algorand finality
Type
Zeitgeist is a parachain, while Algorand is a layer 1 blockchain
Launch Date
Zeitgeist was launched 3 years after Algorand
Zeitgeist vs Algorand Decentralization New
Nakamoto Coefficient
Zeitgeist Nakamoto Coefficient is 15X higher than Algorand Nakamoto Coefficient
Validators
Zeitgeist has 68.47% fewer validators than Algorand
Stake
Zeitgeist stake is 6.12X higher than Algorand stake
Consensus Mechanism
Zeitgeist is Nominated Proof of Stake, while Algorand is Pure Proof of Stake
Governance
Zeitgeist and Algorand governance are both on-chain
Zeitgeist vs Algorand Real-Time TPS Chart
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Zeitgeist Comparisons
About Blockchains
About Zeitgeist
Zeitgeist is a decentralized network designed for establishing, wagering on, and settling prediction markets, enabling users to craft intricate financial agreements on a wide range of subjects. The platform's native currency, ZTG, serves to influence the network's direction and acts as a final recourse for dispute resolution within its decentralized court system.
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.