Introduction

    Flow is a Blockchain network project designed to be the foundation for a new generation of video games and applications, as well as the digital assets that power them. It has a unique architecture that allows it to scale without fragmentation in a secure, fast and simple way. In other words, its speed and performance are superior, and it retains a developer-friendly environment. Flow's platform allows non-fungible tokens (NFTs) to be created, exchanged, bought or sold without intermediaries.

    Launched in 2020 by Dapper Labs, developers of the CryptoKitties video game, it was implemented on the Ethereum network and placed on the market in 2017. However, this network was unable to process it once it went viral. So its developers saw the need to create a new blockchain designed specifically for video games and with ample scaling possibilities. Thus Flow Playground was born with the aim of solving all the technological problems encountered.

    The Flow token (FLOW) is the cryptocurrency of the Flow network. And the starting point of a new type of digital economy, open, participatory and borderless. It was designed as a reserve asset used by developers, validators and users who want to join the Flow network and generate rewards. If Flow Playground is the digital infrastructure, the Flow token is the currency without which the network and the applications on it do not work. FLOW is the energy that keeps the network alive.

    Methods

    In this analysis we will focus on Flow. More specifically, we will analyze the following data:

    • Daily TPM and succeeded TPM on Flow.
    • TPM vs succeeded TPM.
    • Success vs fail rate.
    • Popular event types by success and success rate over time.
    • Daily transactions and succeeded transactions over time.
    • Daily failed transactions by type of event.
    • Daily transactions per blockchain.
    • Daily succeeded transactions per blockchain.
    • TPS per blockchain.
    • Succeeded TPS per blockchain.
    • Success rate by blockchain.
    • Failed rate by blockchain.
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    As we can see in the first chart, the daily TPM on Flow has been successfully executed in almost all transactions since the beginning of May. The end of May has seen a big difference, as 600-800 daily TPMs have been made and only 100-200 daily TPMs have been executed successfully.

    In the second graph, we can clearly see that there is no correlation between the daily TPM and the daily TPM succeeded. Therefore, even if there are more transactions, it does not mean that they are successfully executed.

    Finally, in the last chart, we can see that during the whole month of May there has been a higher percentage of successful transactions than failed transactions. At the end of May we can see that failed transactions have increased, reaching 80% of total transactions. Although there has been a drop, June has started with very good data, reaching almost 100% of successful transactions.

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    In the two previous charts, we have analyzed the events that have the greatest impact on failed transactions. There are three clear events, which are the following:

    • TokensWithdrawn
    • FeesDeducted
    • TokensDeposited

    Although they have always been the events with the most failed transactions, they have been more stable and with less difference with the other events than at the end of May. We can see that there has been a huge growth of failed daily transactions in these three events, representing 80% of the total transactions.

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    In the first graph, we can see that there are three significant points in terms of unsuccessful transactions. The one that stands out the most was at the end of May, because in the other two cases, there were the same daily transactions. On the other hand, at the end of May there was a big difference. There were about 2M transactions and only about 500k were successful. It was during the end of May, the biggest difference between the transactions made and the successful ones.

    As we have analyzed above, the three events with the most failed transactions are: TokensWithdrawn, FeesDeducted and TokensDeposited. We can see that during the whole of May there are few failed transactions, reaching 15k. Still, there is a clear difference during the end of May. These three events, the day they have the most failed transactions, have reached an amount of 929k each.

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    In these graphs we can see that there is a clear difference between the Solana network and the other Blockchain networks. In first place, we find Solana, reaching 40M transactions per day in the month of May. Flow has normal values compared to the other networks. During the month of May it reached a maximum of 600k.

    When we talk about TPMs, Solana continues in first place with a big difference with respect to the other Blockchain networks. This time, Flow has lower values than other networks, such as Ethereum and Algorand.

    Finally, in the last graph, we can see the success rate by Blockchain. First of all, Ethereum has remained at almost 100% of successful transactions throughout May. We can also see that Flow has remained above almost all networks with an average of 90% of transactions successfully executed, but at the end of the month its values have plummeted, reaching less than 20% of successful transactions.

    Key insights

    • The daily TPM in Flow has been successfully executed in almost all transactions since the beginning of May, except for the end of this month, when it has declined considerably.
    • There is no correlation between the daily TPM and the daily TPM succeeded.
    • The whole month of May there has been a higher percentage of successful transactions than failed transactions.
    • The events that have the greatest impact on failed transactions are: TokensWithdrawn, FeesDeducted, TokensDeposited.
    • There has been a huge growth of failed daily transactions in these three events.
    • There is a difference between the Solana network and other Blockchain networks in daily transactions.
    • About TPM, Flow has lower values than other networks.

    Author details

    • Discord Id: cristinatinto#3946
    • Date: 2022-12-09

    Specific Flow speed analysis

    Flow speed comparison against other L1 chains