information on DEXes? Find out what we discussed in Cartesi’s R&D call about an interesting data structure for DEXes👇
https://x.com/cartesiproject/status/1735253461095039285
First of all, we all know DEXes are one of the most popular, tried-and-true applications in web3. They’re the basis of DeFi and single-handedly catapulted the 2021 DeFi summer with the introduction of AMMs and all advances in open finance that come with them.
But does this mean that we’ve already done everything there is to be done about DEXes? Definitely not. The usual way DEXes are implemented is probably not the best way.
The problem with DEXes is that they usually use an automated market maker or AMM. This is great for decentralization, composability, and many other reasons… but it's bad for users who want to be expressive of their trading preferences.
On an AMM you either trade at the price it gives you or you don’t. There’s not a lot of customization. No stop losses, no limit orders, no interesting derivatives.
That’s why many still prefer order book exchanges even though they’re centralized. DApp-specific chains allow developers to come up with scalable order books that serve a large number of transactions.
However, in a decentralized system, looping through many orders in an order book to settle a transaction is not advisable. What if a data structure could improve this? What if there’s a better way to store DEX information scalably?
This is what a simple modification of B+ Trees could do for DEXes. They're a way to build DEXes that use an order book and scale well with solutions like Cartesi Rollups. 🙌
Get into the weeds of how this data structure could work for scaling order book DEXes.
Listen to the R&D call: https://www.youtube.com/watch?v=RDI-GuaWuWw
Retweet: https://x.com/cartesiproject/status/1735253461095039285
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