Solana Blockchain

by Solana Labs

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Tendermint

by Interchain Foundation

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Zilliqa

by Zilliqa

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Solana Blockchain

by Solana Labs

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Tendermint

by Interchain Foundation

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Zilliqa

by Zilliqa

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What problem does this service solve?

Solana allows developers to create DApps with faster performance by separating the consensus process from the recording of transactions.The Tendermint consensus algorithm secures transactions in the Cosmos ecosystem.Zilliqa is building a scalable development platform based on sharding.

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Company Description

The Solana blockchain uses an innovative Proof of History mechanism to confirm transactions that are recorded on the network. Solana is designed to separate the consensus process from the flow of transactions. This is done with a recursive, verifiable delay function that hashes incoming transactions, and recording information as a function of time. Every node on the Solana blockchain is assigned a cryptographic clock that enables the network to determine the time and ordering of transactions, without having to wait for consensus from other nodes. By separating the process of transaction verification from their recording, a higher throughput is achieved without sacrificing network security.

Tendermint is a consensus algorithm that was created by a company called All in Bits. The open source algorithm is Byzantine Fault-Tolerant and uses an authenticated encryption system to secure transactions. The Tendermint consensus mechanism was developed in 2014 for the Cosmos Network. The Interchain Foundation, which is developing the Cosmos Network, continues to employ All in Bits to support Cosmos.

Zilliqa is an innovative blockchain platform that is designed to be more scalable as the network grows. Zilliqa's platform is based on the concept of sharding; which involves breaking a large network of computers into smaller decentralized networks.
Zilliqa's goal is to increase transaction rates as its network expands. The platform is tailored towards enabling secure data-driven decentralized apps that are designed to meet the scaling requirements of machine learning and financial algorithms.

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