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Avalanche’s testnet recently recorded a transaction rate of 143,322 transactions per second (TPS) with its HyperSDK blockchain upgrade, addressing the ‘blockchain trilemma’ of decentralization, security, and scalability.

Ava Labs developed HyperSDK as a framework for developers to construct high-performance Virtual Machines (VMs) on the Avalanche network. The architecture removes the necessity for developers to craft foundational code, simplifying and accelerating custom development.

For context, Avalanche’s current TPS is up to 4,500. In comparison, Solana achieves between 2,000 and 3,000 TPS, and Ethereum processes around 15-20 TPS, according a comparative analysis from Coincodex. Even if HyperSDK’s numbers are reduced by half in real-world scenarios, as suggested by Nick Mussallem, Ava Labs’ head of product, it remains a significant advancement.

Efforts At Operational Harmony

Blockchains, including the technology behind HyperSDK, manage data predominantly as key/value pairs, representing elements ranging from token balances to intricate smart contract details. For the HyperSDK system to operate fluidly, all participants must achieve consensus on this state. Discrepancies, such as differing token amounts among members, can disrupt this unity.

Aligning this state becomes challenging given the expansive amount of data and potential threats from malicious entities. Herein arise two significant challenges: protecting trustworthy HyperSDK participants from endorsing an erroneous state, and attaining consensus despite the data’s enornmity. At the core of HyperSDK’s solution is the Merkle Trie (a trie, in blockchain development, represents a core data structure of data storage), a composite of the Merkle Trees and Radix Tries.

The Merkle Tree, a specialized structure, produces distinct “fingerprints” for its data segments. If there’s a change in the tree’s data, its fingerprint changes as well, allowing HyperSDK to represent the state via this unique fingerprint. When participants share matching fingerprints, it indicates consensus. Variations in these fingerprints signal differing states. Concurrently, the Radix Trie, another tree-like structure, ensures efficient key/value pair storage.

While Merkle Trees are proficient at verifying data, they aren’t tailored for linking keys to values. Integrating these two forms the Merkle Trie, essential to HyperSDK for combining both functions. This structure consists of nodes with key data, value data, and the fingerprints of child nodes. Its condsistency and trustworthiness are maintained by cryptographic hash methods, such as SHA-256, which yield a uniform fingerprint regardless of data input size. These fingerprints, which are crucial to HyperSDK’s functionality, denote both the individual nodes and the entire trie.

HyperSDK and HyperChains

Mussallem emphasizes that the speed increase did not sacrifice decentralization or security. The team reduced certain components of the Ethereum Virtual Machine (EVM) and integrated a distinct consensus algorithm to optimize speed.

HyperSDK allows the creation of subnets, termed HyperChains, offering developers customization options. Coupled with scalability and security features, HyperSDK aims to be a reliable tool in the blockchain sector.

Developers will benefit from a user interface requiring minimal coding. While the choice in VM implies quick deployment, Mussallem mentioned that HyperSDK is currently in “early beta stages” and open-source. A full launch is anticipated by the end of the year.

Disclaimer: This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.