AlDBaran: Towards Blazingly Fast State Commitments for Blockchains

TL;DR

AlDBaran introduces a highly efficient authenticated data structure for blockchains, enabling multi-million TPS state updates with support for historical proofs, surpassing existing solutions in speed and simplicity.

Contribution

It presents AlDBaran, a novel authenticated data structure that eliminates disk I/O, employs prefetching, and refines Merkle tree updates for ultra-fast blockchain state commitments.

Findings

Handles 48 million updates/sec on high-end hardware

Achieves 8 million updates/sec on portable hardware

Supports historical state proofs for new blockchain applications

Abstract

The fundamental basis for maintaining integrity within contemporary blockchain systems is provided by authenticated databases. Our analysis indicates that a significant portion of the approaches applied in this domain fail to sufficiently meet the stringent requirements of systems processing transactions at rates of multi-million TPS. AlDBaran signifies a substantial advancement in authenticated databases. By eliminating disk I/O operations from the critical path, implementing prefetching strategies, and refining the update mechanism of the Merkle tree, we have engineered an authenticated data structure capable of handling state updates efficiently at a network throughput of 50 Gbps. This throughput capacity significantly surpasses any empirically documented blockchain throughput, guaranteeing the ability of even the most high-throughput blockchains to generate state commitments effectively. AlDBaran provides support for historical state proofs, which facilitates a wide array of novel applications. For instance, the deployment of AlDBaran could enable blockchains that do not currently support state commitments to offer functionalities for light clients and/or implement rollups. When benchmarked against alternative authenticated data structure projects, AlDBaran exhibits superior performance and simplicity. In particular, AlDBaran achieves speeds of approximately 48 million updates per second using an identical machine configuration. This characteristic renders AlDBaran an attractive solution for resource-limited environments, as its historical data capabilities can be modularly isolated (and deactivated), which further enhances performance. On consumer-level portable hardware, it achieves approximately 8 million updates/s in an in-memory setting and 5 million updates/s with snapshots at sub-second intervals, illustrating compelling and cost-effective scalability.