By Maelstrom (Arthur Hayes' Family Office)

Compilation: Felix, PANews

Oracle Machine protocol act as a intermediary between the Decentralization network and external data sources, connecting on-chain and off-chain data together in a secure and scalable way. This includes Web APIs, databases, sensors for connected devices, real-time data feeds, and even other Blockchain networks. As Blockchain applications become more complex, this off-chain data becomes increasingly important for the development of new use cases (such as the recently popular "machine learning").

In this article, we'll take a deep dive into three key Oracle Machine protocol, Chainlink, Pyth, and Flare. Although Chainlink is currently a market leader, there are limitations to latency and high throughput; Pyth, on the other hand, focuses on financial institutions and lacks universality. Notably, the "dark horse" Oracle Machine protocol Flare, a protocol that combines features comparable to Chainlink and Pyth with fully sovereign L1 and is a unique (and possibly underestimated) protocol. Here's an in-depth look at each protocol and what is known as the "Battle of Oracle Machine."

LINK

Chainlink is synonymous with Oracle Machine and is the undisputed market leader. Its robust Decentralization Node network makes Chainlink the go-to choice for long dApps, DEXs, and Decentralized Finance platforms. Chainlink's reliability and growing number of partners make it a top choice for institutions and emerging projects. Chainlink's decentralized oracle network operates through a unique consensus mechanism that leverages longest nodes to acquire and verify real-world data. This longer approach ensures transparency and minimizes the risk of manipulation. However, while Oracle Machine network itself is Decentralization, analysts note that Chainlink's multisignature maintains a high degree of control over protocol price feeds. To ensure data accuracy and tamper-proofing, Chainlink uses economic incentives to align the interests of Node operators and users.

As of May 2024, Chainlink integrates with longest 500 DEXs and longest Decentralized Finance platforms. Its Oracle Machine provides price information for more than 5,000 trading pairs, with update times ranging from minutes to hours depending on the chain and asset. Chainlink heartbeats are refreshed periodically, or when the price deviates by more than a specified amount (e.g., 1%).

Chainlink Oracle Machine is currently worth more than $20 billion across different data sources and services. LINK Token is used for staking and reputation within the Chainlink network, with a market capitalization of over $7 billion. According to Coingecko, Chainlink Token accounts for more than 70% of all Oracle Machine market capitalization. Overall, the demand for Chainlink Oracle Machine services adds value to Token holders, as LINK pays Node Operators for the service.

(The total guaranteed value of the Oracle Machine is TVS, which is longest used to summarize the overall economic impact and adoption of the Oracle Machine network.) Source: *DefiLlama )

It's worth noting that the Oracle Machine market isn't static, and competitors are constantly grabbing the pie.

PYTH

Pyth is a new Oracle Machine protocol focused on financial use cases, using long 90 TradFi and encryption Financial Institution as data providers (considering price data for stocks, commodities and coin directly from the source). Pyth's innovation is threefold:

1. Quantifying Uncertainty: Introducing confidence intervals in their reported prices, the feature allows users to measure not only the price, but also the degree of uncertainty in the price, which is extremely valuable in Fluctuation markets.
2. Longest chains: Pyth's data sources can be used for almost any on-chain application. Originally launched on Solana and its own Pythnet, a fork of the Solana codebase, Pyth Network provides solutions for non-Solana chains through integrations such as Wormhole.
3. Efficient Price Updates: Another innovation introduced by Pyth Network is the Pull Oracle architecture, which achieves the efficient, on-demand price updates that data users demand, unlike the inefficient Push Oracle that is common in legacy systems.

Pyth's price refresh rate is typically between 300 and 500 milliseconds, which is orders of magnitude faster than some competitor services, or better suited to the needs of modern finance (e.g., DEXs). This speed is attributed to Pyth's trust model, which relies directly on several large data providers rather than Node Decentralization to provide price information. Pyth's trust model isn't the only module with a low degree of decentralization. Pyth's reliance on centralized entities such as Wormhole has made it vulnerable to outages in the past. Pyth is also working to implement data provider staking requirements to incentivize accurate price feed services.

Still, Pyth's TVS has surged from $500 million to long $4 billion in the past six months, fueled by borrowing protocol. Pyth's partnership with Solana has been very successful, combining fast data processing with Solana's high-throughput infrastructure. Following a successful Airdrop last November, Pyth plans to offer a new round of $100 million worth of Pyth Tokens to its longest integrated dapp partners.

While Pyth has been successful in its specific market, it has yet to prove to scale beyond the financial sector for a wider range of use cases.

FLR

Flare is an emerging contender in the Oracle Machine space, taking a different approach than Chainlink, Pyth, and other competitors. That is, Flare is not just an Oracle Machine network, it also has computing power - that is, EVM smart contracts. Flare combines a smart contracts platform with an Oracle Machine system, and the validators responsible for network consensus and generating blocks are also responsible for transmitting data to the network. That is, validators need to successfully provide accurate data to the network in order to receive validation rewards. Google Cloud recently joined Flare as a validator and contributor, along with companies such as Figment and Ankr.

Data connectors and the Flare Time Series Oracle Machine (FTSO) are at the heart of the Flare system:

• Data Connectors: Bring state data from other Blockchain and web services into the Flare Blockchain, such as transaction information.
• FTSO: Transfer time series data from longest chains to Flare. (The ongoing upgrade will eventually deliver long up to 1000 data sources every 90 seconds, as well as 1-2 block updates)

This unique combination is what sets Flare apart in that data feeds and proofs are free for dapps that run directly on Flare (Flare charges for data elsewhere).

All in all, Flare is probably underrated.

Chainlink has a considerable first-mover advantage, with countless projects already integrating with it. However, as Flare gains more and more long attention, it is possible to quickly catch up with Chainlink. To better illustrate the potential of FLR, the following is the FDV as of May 1, 2024:

• FLR: $2.9 billion
• PYTH: $5 billion
• LINK: $12.7 billion

These comparisons may be quite different when you consider the following backgrounds:

• Flare's projects have less than 10% of Chainlink's integrations and are just getting started
• FLR's tokenomics incentivizes the active participation of stakeholders and holders
• Flare provides both data and computing services, making it very different from existing Oracle Machine protocol – in addition to being able to generate fees from data services, it can also build its own native ecosystem

Flare's development is still early, but it is assumed that a development path can be achieved – here are the rising potential of FLR in different scenarios:

• Same as PYTH: about 1.7 times
• Half of LINK: Approximately 2.27 times
• The median value of PYTH and LINK: about 3.17 times
• 75% of LINK: about 3.3 times

Projects that not only meet current market needs, but also address the challenges of the next generation will win the battle of the Oracle Machine. While Chainlink is the market leader, latency and applicability for high-throughput use cases leaves longing for improvement. Pyth's focus on Financial Institution, on the other hand, brings a unique dimension to the Oracle Machine domain, but leaves a long short blank in terms of universality across use cases. Flare combines the above characteristics with the characteristics of L1, and its unique market positioning is worth paying attention to. The winner of this war will be the protocol that can provide reliable, up-to-date data, create powerful network effects, and adapt to the changing needs of Decentralized Finance ecosystems (including emerging ecosystems such as artificial intelligence, which involve dealing with large and long diverse datasets). While it's too early to tell, FLR seems to be undervalued compared to the same track Token.

Related reading: Behind the monthly pump of Flare Token by more than 100%: update tokenomics and increase investment in ecological construction