Chainlink’s New Technology Eliminating Delays on the Network: “Data Streams”

Chainlink has launched a feature called Data Streams to reduce network latency. According to the company’s statement, the primary purpose of Data Streams is to provide an alternative and transparent infrastructure to centralized exchanges.

Decentralized computing platform Chainlink announced a new and comprehensive application version called “Data Streams“. This decentralized data solution intermediary aims to solve the latency issue on the network by using a “pull-based” system that continuously makes high-speed market data available. The proposal entered early access on the layer 2 platform, Arbitrum.

What is a Pull-based System?

A pull-based system increases the speed of data updates, thereby reducing the delay in how quickly data reaches from one place to another. In distributed networks, latency is a frequently encountered issue due to the time it takes for information to spread to different points. This situation slows down the completion of transactions and the synchronization of data.

A Rival to Centralized Exchanges is Coming

Chainlink co-founder Sergey Nazarov stated that data streams could compete with centralized exchanges by increasing the execution speeds of DeFi protocols, and they will achieve this with a fair, transparent, and decentralized infrastructure.

“Data Streams not only enables DeFi (decentralized finance) protocols to support execution speeds and a user experience that rival centralized exchanges, but to do so without compromising on the core Web3 value of fair, transparent, and decentralized infrastructure.”

Sergey Nazarov.

Chainlink, in addition to Data Streams, also introduced new decentralized computing capabilities on the mainnet with Functions Beta and Automation 2.0. Chainlink functions offer developers the ability to connect decentralized applications to any application programming interface (API), and additionally, help them to transfer data between systems more efficiently.

Source: Coindesk

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