Lambda256, the Blockchain technology subsidiary of Dunamu, said on the 13th that Web3-focused research firm Tiger Research introduced the on-chain (Blockchain network) data platform "DataShare" as a representative example of on-chain data infrastructure for traditional finance.
Tiger Research's "on-chain data infrastructure analysis report" said that although on-chain data is open to everyone, its structure makes it difficult for traditional finance to use as is. It introduced Lambda256's DataShare as a case that addresses this.
According to the report, while the existing financial system operates on standardized structured data, on-chain data is closer to raw data that requires separate indexing (the task of creating lists or tables to classify), decoding (the process of reverting to the original form or a human-readable language), and normalization.
In the early days of the virtual asset market, participants and transaction volumes were limited, so these issues did not surface, but as asset classes diversify and transaction volumes expand, the standards required of on-chain data infrastructure are rising.
Tiger Research explained that on-chain data infrastructure is not simply the building of databases, but a large-scale infrastructure operation that must index differing data structures across chains in real time and continuously respond to new standards and chain upgrades. It said leveraging a proven professional partner is a practical alternative and introduced Lambda256's DataShare as a case that meets these requirements.
DataShare uses its own indexing engine to provide data from a multi-chain (connecting multiple, different Blockchain networks) environment as a dataset of normalized data aligned with financial institutions' existing workflows. The collected data undergoes cross-verification against the Blockchain ledger.
The report also introduced use cases of DataShare. As cases of issuing listed stocks as Blockchain-based tokens increase, including by Galaxy Digital and Securitize, brokerages face a new task of accurately determining token holdings on each dividend date or voting date.
Tiger Research said DataShare refines transaction data dispersed across multiple chains into a format that can be used immediately in existing financial systems and has secured performance capable of processing about 20,000 transactions per second per chain in real time.