Handle concurrency in a market crash
How does Danogo handle concurrency in a market crash?
Danogo is implementing parallel liquidation processing to avoid the bottlenecks seen in Indigo/Liqwid’s system during high-volatility events. Here’s how Danogo’s approach improves on existing Cardano DeFi architectures:
1. Parallel Execution for Liquidations & Collateral Top-Ups
Indigo utilize traditional model where liquidation happens sequentially (one after another)
Liqwid utilize batchers to allow 4 or 8 liquidations to happen at the same time depends on each token market, but incur batching cost and market interruption during frequent batching.
Unlike Indigo/Liqwid models, Danogo does not use batcher and decouples each loan from the main pool.
This means every loan operates on its own execution thread, allowing:
Simultaneous liquidations, reducing delays during mass liquidations.
Faster collateral top-ups, giving borrowers real-time protection from liquidation.
2. Eliminating Liquidation Queues
In Indigo’s case, a single liquidation bot had to process each transaction one by one, leading to a two-hour queue during the ADA flash crash in 2023.
Danogo’s multi-threaded execution model ensures that no loan has to wait for another before being processed.
3. Open-Source Liquidation Bot Infrastructure
Danogo will provide technical documentation and APIs so that anyone can run their own liquidation bot.
This means that instead of relying on a single entity (which creates a bottleneck), multiple liquidation bots can run concurrently, leading to:
Faster liquidation processing.
Reduced risks of bad debt accumulation.
Increased decentralization, as liquidations are no longer controlled by a single entity.
Why This Matters?
Prevents Bad Debt: Faster liquidation prevents loan collateral from falling below the borrowed amount.
Ensures Market Stability: Borrowers can top-up collateral in real-time, reducing unnecessary liquidations.
Decentralization & Open Participation: By making liquidation tools publicly accessible, Danogo avoids centralization risks while improving system efficiency.
This approach significantly improves scalability, efficiency, and fairness in Cardano’s DeFi ecosystem. 🚀
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