A Cross-Chain Event-Driven Data Infrastructure for Aave Protocol Analytics and Applications

TL;DR

The paper tackles the lack of standardized cross-chain, event-level datasets for DeFi protocols by introducing the first comprehensive event-driven data infrastructure for Aave V3 across six Ethereum-compatible chains. It presents an open-source Python pipeline that decodes eight core events, yielding over 50 million records with rich metadata and USD valuations, and applies automatic sharding to ensure reproducibility and chronological integrity. The resulting Zenodo dataset enables granular analyses of capital flows, interest-rate dynamics, liquidation cascades, and cross-chain user behavior, serving as a foundational resource for systemic risk and multi-chain DeFi studies. The work provides practical impact by enabling researchers and practitioners to perform robust cross-chain analytics and benchmarking across diverse deployments.

Abstract

Decentralized lending protocols, exemplified by Aave V3, have transformed financial intermediation by enabling permissionless, multi-chain borrowing and lending without intermediaries. Despite managing over $10 billion in total value locked, empirical research remains severely constrained by the lack of standardized, cross-chain event-level datasets. This paper introduces the first comprehensive, event-driven data infrastructure for Aave V3 spanning six major EVM-compatible chains (Ethereum, Arbitrum, Optimism, Polygon, Avalanche, and Base) from respective deployment blocks through October 2025. We collect and fully decode eight core event types -- Supply, Borrow, Withdraw, Repay, LiquidationCall, FlashLoan, ReserveDataUpdated, and MintedToTreasury -- producing over 50 million structured records enriched with block metadata and USD valuations. Using an open-source Python pipeline with dynamic batch sizing and automatic sharding (each file less than or equal to 1 million rows), we ensure strict chronological ordering and full reproducibility. The resulting publicly available dataset enables granular analysis of capital flows, interest rate dynamics, liquidation cascades, and cross-chain user behavior, providing a foundational resource for future studies on decentralized lending markets and systemic risk.

Figures (8)

• Figure 1: Supply logic of Aave V3 protocal.
• Figure 2: Withdraw logic of Aave V3 protocal.
• Figure 3: Borrow logic of Aave V3 protocal.
• Figure 4: Repay logic of Aave V3 protocal.
• Figure 5: Basic .