>
> A ‘Green’ solution, Algorand is the world’s most decentralized, scalable, and secure blockchain infrastructure. > > From DeFi to NFTs, Algorand aims to enable a world where everyone creates and exchanges value efficiently, transparently, and securely.

> Algorand Features: > > Folks Finance - The Leading Capital Markets Protocol for borrowing and lending.

> AlgoFi - The DeFi hub, with DEX, lending and stablecoins. > > Tinyman - Decentralized trading protocol. > > AlgoDex - Decentralized marketplace with on-chain orderbook.

Algorand - Transactions by Protocol

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Objective:

Looking at Folks Finance, AlgoFi, Tinyman, and AlgoDex, what percent of transactions do their app calls and associated transactions make up on the Algorand blockchain?
How have the number of transactions changed over time for each Protocol?
How much in fees have been spent on transactions relating to each protocol?
What % of all application users have used each protocol?
Has the price of ALGO been an influence on the number of transactions produced by each protocol?

Notes:

App ID lists provided by Flipside Crypto.

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🔗 Links:

➡️ Visit Algorand

📜 Read the Docs

🐦 @Algorand

What percent of transactions do their app calls and associated transactions make up on the Algorand blockchain. ⤵️

Technique:

Take all Tx from flipside_prod_db.algorand.transactions
Left join flipside_prod_db.algorand.application_call_transaction on TX_ID
Case statement on App Id’s to categorize all Tx

How have the number of transactions changed over time for each Protocol? ⤵️

Technique:

Utilizing the tables above, add Bock_Time as a dimension to the grouping.
Utilize area to represent % of the whole to observe change over time.

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🗝️ Points:

Asset transfers and payments dominate Algorand transactions taking up over 90% of all activity, this leaves our applications with less than 5% of overall activity.
Digging deeper, we find that among application calls, our apps represent ~ 50% of all transactions of this type.
AlgoFi and Tinyman activity far outweighs Folks Finance and Algo Dex.

🗝️ Points:

The first chart presents the macro view of Algorand where we observe a transition from payments to asset transfers (NFTs) and then a growing development of DeFi and other applications.
In approx 1 year these applications have grown to represent ~ 15% of all Algorand transactions.
Focusing on our four applications, we observe Tinyman loosing volume and being overtaken by AlgoFi.
Currently, we begin to see Folks Finance gain a small amount of traction.

How much in fees have been spent on transactions relating to each protocol? ⤵️

Technique:

Filter the initial table by protocols required and sum fees.
Calculate total and accumulation over time.

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🗝️ Points:

Fees follow the activity we observed among the four protocols.
While Tinyman has been active longer than AlgoFi, it has realized less in overall fees.
Note that the charts use different scales based on their respective volumes.

What % of all Application users have used each protocol? ⤵️

Technique:

Utilize all application calls.
Calculate distinct senders overall and by protocol to calculate percentage of whole.

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Has the price of ALGO been an influence on the number of transactions produced by each protocol? ⤵️

Technique:

Aggregate daily ALGO price and daily Tx count per protocol.
Utilize a scatter plot to determine if a relationship exists.

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🗝️ Points:

Of our four applications, Tinyman has been used by 2.3% of all application users on Algorand.
While percentages are small, they have been achieved in a short amount of time with respect to the age of the blockchain.
As financial activities grow on Algorand, we can expect to see an increased share of users interacting with the platforms.

🗝️ Points:

Of our four applications Tinyman and Algo Dex demonstrate the strongest linear relationship between price and transaction, where increased prices have a positive correlation with increased transactions.

🤔 Conclusion:

We have observed a transition of activity on Algorand from payments to asset transfers and now a growing application usage.
AlgoFi, Tinyman, Algo Dex, and Folks Finance respectively represent close to 50% of all application transactions which consume roughly 15% of all transactions.
The majority of this activity has shifted from Tinyman to AlgoFi.*The difference in fees generated between AlgoFi/Tinyman and Algo Dex/Folks Finance is significant.
With Tinyman and Algo Dex we observe the strongest positive correlations between ALGO price and transactions. The strength of these correlations, however, is not strong.