Technology Category
Data Mining & Knowledge Management: Scalability, Parallel & Distributed SystemsSearch and Optimization: Distributed SearchMachine Learning: Hardware-aware ML
AlDBaran: Towards Blazingly Fast State Commitments for Blockchains
🤖 AI Summary
To address the bottleneck of authenticated databases failing to sustain tens of millions of transactions per second (TPS) in high-throughput blockchains, this paper proposes an ultra-fast state commitment system. Our method eliminates disk I/O from the critical path, integrates prefetching with incremental Merkle tree updates, and supports modular historical data management—dynamically disableable for flexibility. By combining in-memory state residency with a lightweight snapshot mechanism, we achieve efficient state updates and verifiable historical proofs. Experimental results show a peak update throughput of 48 million operations per second under identical hardware configurations; on consumer-grade hardware, the system achieves 8 million updates/sec in pure in-memory mode and 5 million updates/sec in snapshot mode—significantly outperforming existing approaches. This work delivers a verifiable, scalable state root infrastructure essential for next-generation high-performance blockchains.
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Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Enables blazingly fast state commitments for high-throughput blockchains
Supports historical state proofs for novel blockchain applications
Achieves superior performance in resource-limited environments
Innovation
Methods, ideas, or system contributions that make the work stand out.
Eliminates disk I/O from critical path
Implements prefetching and Merkle tree optimizations
Supports historical state proofs for scalability
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