Arbitrum vs Binance: Comparison

    Introduction

    This dashboard compares the two blockchains: Arbitrum and Binance. I will compare the number of transactions, transfers, and daily users, as well as the ETH/BNB volumes and the transaction fees for each blockchain in the past seven days, side by side first, and then combine the results into cohesive comparison charts.

    Let’s begin the analysis by looking at the number of transactions and transfers for each blockchain.

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    As we can see, Arbitrum dominates Binance when it comes to the number of transfers and transactions by quite a lot - this is quite a surprising result to me, I expected to see the opposite. I am not sure why this is the case here, but it is possible that Flipside’s Binance tables are missing some transactions and hence the count is a lot lower than it is in reality.

    The next step is to look at the number of daily users for each network.

    Daily users

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    The charts above tell us that for the first 3 days in the past week, Binance was the winning network when it comes to daily, unique users. During the rest of the week, Arbitrum took over, with the peak count being almost 60k users on the 29th of June 2022!

    Transfer Volume

    Let’s now look at the volumes transacted on each blockchain. I will first look into the volume in the native assets, that is ETH for Arbitrum and BNB for Binance, and look at how the volumes compare to the daily count of unique users. As it does not make sense to compare the ETH volume with BNB volume, because no one wants to compare apples to oranges, I will instead compare the USD volume for both networks.

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    As we can see, the USD volume on Arbitrum is much higher than on Binance - again, this seems slightly counter-intuitive to me, and could be because Binance’s data is missing…

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    For Binance, we can see how much BNB users spend to make their transactions on a daily basis. For Arbitrum, initially, I had some trouble plotting these results, as, on the 29th of June, the data tells us that 10^63 ETH has been paid for fees, which is definitely not the case! Having investigated this a step further, the tx_hash:0x62b7f8049679e7509ace9ed2e58579b83c8670d73f467a1e1cfa95076033c76adata error resulted in this colossal outlier of billion of billions+ of ETH, even though in reality this transaction cost only 0.0002 ETH. Removing this transaction from the data set resolved this issue, and now we can see the transaction fees for each network clearly, side by side.

    Conclusion

    This dashboard has looked into how Arbitrum and Binace are doing in comparison to each other. I have looked into the number of transactions and transfers made on each network in the past seven days, as well as the volumes of native assets (ETH and BNB) together with the USD volumes and the daily unique users. We have found out that Arbitrum dominates Binance in most of those categories, which was quite a surprising result to me.

    I hope you found this comparison insightful! 😌

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    The assumption stated above does not really stand here, we can see that on Arbitrum, on June 27th and June 30th, the number of daily users stays constant at around 45k, whereas the USD volume varies by quite a large amount. We can see that on June 27th, the marker is black, indicating a volume of over $80M, whereas on 30th of June, this amount decreases to around $60M. This is an interesting result, as it implies that on 27th June users were making larger transactions on average (with the possibility of more whales on that day, compared to 30th of June).

    For Binance the assumption does not stand either - what is really interesting here is that on July 1st, the volume transacted was the greatest, even though the number of unique users is the smallest (note: the data for today is incomplete as we are only half-way through the day, however we can see that the USD volume is already much greater at this point in time in comparison to earlier days).

    Daily transaction fees

    In this last section of this dashboard, I will investigate the daily amount of fees spent for transactions on both networks.

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    Correlations

    Let’s look into the assumption that the more daily users there are, the more USD is being transacted on both networks.