Waves Sets Record for Maximum Transactions Per Day

We are very excited to announce that our platform has processed more transactions in 24 hours than any other open blockchain in existence.

On Sunday 21 October the Waves network processed a remarkable 6.1 million transactions on MainNet.

Statistics from http://dev.pywaves.org/txs/ show a total of 108,741 transactions, including 60,933 MassTransfers — a special kind of Waves transaction that can hold 100 transfers at once, for faster and more efficient processing. A total of 6,141,108 transfers was processed by the network, with the blockchain supporting hundreds of transactions per second at peak times.

While Bitcoin is the best-known blockchain and holds the most value, its capacity is notoriously limited, making it unsuitable for mass-market applications and microtransactions. ‘Bitcoin processes just a few transactions per second,’ comments Sasha Ivanov, Waves CEO and founder. ‘Ethereum’s capacity is into double-digit tps, and a handful of other blockchains have improved on this incrementally in various ways. Waves has implemented tech that enables a step-change in transaction volumes — not just in the lab but in the real world, on MainNet, as these figures prove beyond doubt.’

Figures from Bitinfocharts show that even leading blockchain platforms have posted no more than 2 million txs/day throughout their entire history. A number of blockchain protocols promise very high throughput, but this is typically theoretical (at this point) or on TestNet — a closed environment that is far more controlled and favourable than MainNet.

Waves’ success is down to its use of Waves-NG, a consensus algorithm adapted from the Bitcoin-NG scaling proposal suggested by Cornell professor Emin Gun Sirer. Miners are chosen in advance and transactions processed into the blockchain in near-realtime, with the chief delay being network latency. ‘Along with other advances, this enables us to do what no other open blockchain platform has ever achieved,’ continues Ivanov. ‘And we have further optimisations we can make to improve capacity still further.’

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