Tendermint

by Interchain Foundation

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APIS

by The Oxchild Pte Ltd.

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Zilliqa

by Zilliqa

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Tendermint

by Interchain Foundation

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APIS

by The Oxchild Pte Ltd.

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Zilliqa

by Zilliqa

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What problem does this service solve?

The Tendermint consensus algorithm secures transactions in the Cosmos ecosystem.APIS will allow users to invest their coins on a network masternode without having to stake a large number of coins or deal with the technical requirements of setting one up.Zilliqa is building a scalable development platform based on sharding.

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Company Description

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.

APIS is developing a masternode mediation platform that will lower the barriers of entry for users wanting invest their coins on their own masternode of a network. A masternode is a type of node that has additional voting influence and block rewards, on a Proof-of-Stake network. Investors are able to place coins on a masternode and receive a stable interest from the block rewards; similar to interest that is given in a bank. APIS will allow users to invest in masternodes without having to deal with the technical requirements or stake a prohibitively large number of coins.
Their network is powered by the Ethereum-based APIS token.

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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