The War of Oracles, why is Flare underestimated?

Author: Maelstrom, Arthur Hayes' family office

Compiled by: Felix, PANews

Oracle protocols act as intermediaries between decentralized networks and external data sources, securely and scalably connecting on-chain and off-chain data. This includes Web APIs, databases, sensors from connected devices, real-time data feeds, and even other blockchain networks. As blockchain applications become increasingly complex, this off-chain data is becoming more critical for the development of new use cases (such as the recently popular "machine learning").

This article will delve into three key oracle protocols: Chainlink, Pyth, and Flare. While Chainlink currently holds a market-leading position, it faces limitations in latency and high throughput; Pyth, on the other hand, focuses on financial institutions and lacks universality. Notably, the "dark horse" oracle protocol Flare combines functionalities comparable to Chainlink and Pyth with a fully sovereign L1, making it a unique (and potentially underestimated) protocol. Below, we will explore each protocol in depth and discuss the so-called "oracle wars."

LINK

Chainlink is synonymous with oracles and is the undisputed market leader. Its robust decentralized node network makes Chainlink the preferred choice for many dApps, DEXs, and DeFi platforms. Chainlink's reliability and growing partnerships have made it the go-to option for institutions and emerging projects. Chainlink's decentralized oracle network operates through a unique consensus mechanism that utilizes multiple nodes to source and verify real-world data. This multi-party approach ensures transparency and minimizes the risk of manipulation. However, while the oracle network itself is decentralized, analysts point out that Chainlink's multi-signature maintains a high level of control over the protocol's price feeds. To ensure data accuracy and tamper-resistance, Chainlink employs economic incentives to align the interests of node operators and users.

As of May 2024, Chainlink has integrated with over 500 DEXs and more than 800 DeFi platforms. Its oracles provide price information for over 5,000 trading pairs, with update times ranging from minutes to hours depending on the chain and asset. Chainlink heartbeats refresh regularly or when prices deviate beyond a specified threshold (e.g., 1%).

Chainlink oracles currently hold over $20 billion in value across various data sources and services. The LINK token is used for staking and reputation within the Chainlink network, with a market cap exceeding $7 billion. According to Coingecko data, LINK tokens account for over 70% of the total oracle market cap. Overall, the demand for Chainlink's oracle services has allowed token holders to realize appreciation, as LINK needs to pay node operators for service fees.

The total collateral value of oracles TVS * is often used to summarize the overall economic impact and adoption of oracle networks. Source: * DefiLlama

It is worth noting that the landscape of the oracle market is not static, and competitors are constantly vying for a piece of the pie.

PYTH

Pyth is a new oracle protocol focused on financial use cases, utilizing over 90 TradFi and crypto financial institutions as data providers (directly sourcing price data for stocks, commodities, and currencies). Pyth's innovations can be summarized in three aspects:

1. Quantifying uncertainty: Introducing confidence intervals in its reported prices, allowing users to gauge not only the price but also the degree of uncertainty, which is highly valuable in volatile markets.
2. Multi-chain: Pyth's data sources can be utilized by applications on almost any chain. The Pyth Network initially launched on Solana and its own Pythnet (a fork of the Solana codebase), providing solutions for non-Solana chains through integrations like Wormhole.
3. Efficient price updates: Another innovation introduced by the Pyth Network is the Pull Oracle architecture, which enables efficient, on-demand price updates as requested by data users, unlike the inefficient Push Oracle commonly found in traditional systems.

Pyth's price refresh rate typically ranges from 300 to 500 milliseconds, significantly faster than some competitors' services, better meeting the demands of modern finance (e.g., DEXs). This speed is attributed to Pyth's trust model, which directly relies on several large data providers rather than decentralized nodes to provide price information. Pyth's trust model is not the only module with a lower degree of decentralization. Pyth's reliance on centralized entities like Wormhole has made it susceptible to disruptions in the past. Pyth is also working to implement staking requirements for data providers to incentivize accurate price feed services.

Despite this, driven by lending protocols, Pyth's TVS has surged from $500 million to over $4 billion in the past six months. Pyth's collaboration with Solana has been highly successful, combining rapid data processing with Solana's high-throughput infrastructure. Following a successful airdrop last November, Pyth plans to offer a new round of Pyth tokens valued at $100 million to its 160+ integrated dApp partners.

While Pyth has achieved success in its specific market, it has yet to prove its scalability to broader use cases beyond finance.

FLR

Flare is an emerging competitor in the oracle space, taking a different approach than Chainlink, Pyth, and other competitors. Specifically, Flare is not just an oracle network but also possesses computational capabilities—namely, EVM smart contracts. Flare combines a smart contract platform with an oracle system, where the validators responsible for network consensus and block generation are also responsible for transmitting data to the network. In other words, validators must successfully provide accurate data to the network to earn validation rewards. Google Cloud recently joined Flare as a validator and contributor alongside companies like Figment and Ankr.

Data connectors and Flare Time Series Oracle (FTSO) are central to the Flare system:

• Data connectors: Bring state data from other blockchains and web services onto the Flare blockchain, such as transaction information.
• FTSO: Transmits time series data from multiple chains to Flare. (Ongoing upgrades will ultimately enable up to 1,000 data sources to be provided every 90 seconds, along with 1-2 block updates.)

This unique combination sets Flare apart, as data feeding and proof are free for dApps running directly on Flare (Flare charges for data from other sources).

In summary, Flare may be underestimated.

Chainlink has a significant first-mover advantage, with countless projects already integrated with it. However, as Flare gains more attention, it could quickly catch up to Chainlink. To better illustrate FLR's potential, here are the FDVs as of May 1, 2024:

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

Considering the following context, the above comparisons may differ significantly:

• The number of project integrations for Flare is less than 10% of Chainlink's, and it is just getting started.
• FLR's tokenomics incentivizes active participation from stakeholders and holders.
• Flare provides both data and computational services, making it fundamentally different from existing oracle protocols—beyond generating fees from data services, it can also build its own native ecosystem.

Flare is still in its early stages, but assuming it can achieve its development roadmap—here are the potential upsides for FLR in different scenarios:

• On par with PYTH: approximately 1.7x
• Half of LINK: approximately 2.27x
• Midpoint between PYTH and LINK: approximately 3.17x
• 75% of LINK: approximately 3.3x

Projects that not only meet current market demands but also address next-generation challenges will win the oracle wars. While Chainlink is the market leader, there is much room for improvement regarding latency and applicability to high-throughput use cases. On the other hand, Pyth's focus on financial institutions brings a unique dimension to the oracle space but leaves many gaps in cross-use case universality. Flare combines these characteristics with the features of L1, making its unique market positioning worthy of attention. The victor of this war will be the protocol that can provide reliable, up-to-date data, create strong network effects, and adapt to the ever-changing demands of the DeFi ecosystem (including emerging ecosystems like AI that involve processing large and diverse datasets). While it is still too early to draw conclusions, FLR appears to be undervalued compared to tokens in the same race.