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, sensor data from connected devices, real-time data feeds, and even other blockchain networks. As blockchain applications become increasingly complex, these off-chain data sources are becoming more crucial for developing new use cases (such as the recent trend of “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 terms of latency and high throughput. Pyth focuses on financial institutions and lacks universality. It is worth noting the “dark horse” oracle protocol Flare, which combines functionality comparable to Chainlink and Pyth with fully sovereign L1, making it a unique (and possibly underestimated) protocol. Below, we will explore each protocol in-depth and offer perspectives on what’s dubbed the “Oracle Wars’’.

LINK

Chainlink is synonymous with oracles and is undisputedly the market leader. Its robust decentralized node network makes Chainlink the preferred choice for many dApps, DEXs, and DeFi platforms. The reliability of Chainlink and its growing list of partners make it the top choice for institutions and emerging projects. Chainlink’s decentralized oracle network operates through a unique consensus mechanism, utilizing multiple nodes to fetch and verify real-world data. This multi-party approach ensures transparency and minimizes manipulation risks. However, while the Oracle network itself is decentralized, analysts point out that Chainlink’s multi-signature controls maintain a high level of control over protocol 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 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 are set for periodic refreshes or when prices deviate beyond a specified range (e.g., 1%).

Chainlink’s oracles currently secure 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 capitalization exceeding $7 billion. According to Coingecko data, the LINK token represents over 70% of the total Oracle market capitalization. Overall, the demand for Chainlink oracle services has enabled token holders to realize appreciation, as LINK is required to pay service fees to node operators.

(The total guaranteed value of an oracle, TVS, is often used to summarize the overall economic impact and adoption of the oracle network. Source: DefiLlama ）

It is worth noting that the pattern of the Oracle market is not static, and competitors are constantly grabbing this piece of cake.

PYTH

Pyth is a new oracle protocol focused on financial use cases, utilizing over 90 TradFi and crypto financial institutions as data providers (sourcing price data directly from the origin for stocks, commodities, and currency). Pyth’s innovation encompasses three aspects:

1. Quantifying Uncertainty: Introducing confidence intervals in its reported prices allows users not only to gauge prices but also to measure the level of uncertainty in prices, which is highly valuable in volatile markets.
2. Multi-Chain: Pyth’s data sources can be used for almost any on-chain application. Initially launched on Solana and its own Pythnet (a branch of the Solana codebase), the Pyth Network provides 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. Unlike the inefficient Push Oracle commonly found in traditional systems, this architecture achieves efficient, on-demand price updates requested by data users.

Pyth’s price refresh rate typically ranges from 300 to 500 milliseconds, several orders of magnitude faster than some competitors’ services, or better suited to meet the demands of modern finance (e.g., dex). This speed is attributed to Pyth’s trust model, which relies directly on several large data providers rather than decentralized nodes to provide price information. Pyth’s trust model is not the only one with a low degree of decentralization. Pyth’s reliance on centralized entities like Wormhole has made it susceptible to interruptions in the past. Pyth is also working on implementing data provider staking requirements to incentivize accurate price feed services.

Nevertheless, driven by lending protocols, Pyth’s TVS has surged from $500 million to over $4 billion in the past 6 months. Pyth’s collaboration with Solana has been highly successful, combining fast data processing with Solana’s high-throughput infrastructure. Following a successful airdrop in November last year, Pyth plans to provide a new round of $100 million worth of Pyth tokens to its over 160 integrated dapp partners.

While Pyth has found success in its specific market, it has yet to prove itself in expanding to broader use cases beyond the financial sector.

FLR

Flare is an emerging competitor in the oracle field, taking a different approach from Chainlink, Pyth, and other competitors. That is to say, Flare is not just an oracle network but also has computational capabilities—specifically, EVM smart contracts. Flare combines the smart contract platform with the oracle system, where validators responsible for network consensus and block generation are also responsible for transmitting data to the network. In other words, validators need to successfully provide accurate data to the network to receive validation rewards. Recently, Google Cloud joined Flare as a validator and contributor, along with companies like Figment and Ankr.

Data connector and Flare Time Series Oracle (FTSO) is the core of the Flare system:

1. Data connector: Bring state data from other blockchains and web services onto the Flare blockchain, such as transaction information.
2. FTSO: Transfer time series data from multiple chains to Flare. (Ongoing upgrades will eventually enable up to 1000 data sources, and 1-2 block updates every 90 seconds)

This unique combination sets Flare apart, with data feeding and attestation being free for dapps running directly on Flare (Flare charges for data elsewhere).

All in all, Flare is probably underrated.

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

1. FLR: $2.9 billion
2. PYTH: $5 billion
3. LINK: $12.7 billion

The above comparison may be quite different if the following background is also considered:

1. Flare’s number of project integrations is less than 10% of Chainlink’s, and it’s just getting started.
2. FLR tokenomics incentivizes the active participation of stakeholders and holders.
3. Flare provides both data and computing services, making it distinct from existing Oracle protocols - in addition to being able to generate fees from data services, it can also build its native ecosystem.

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

1. On par with PYTH: approximately 1.7 times
2. Half of LINK: approximately 2.27 times
3. Midpoint between PYTH and LINK: approximately 3.17 times
4. 75% of LINK: approximately 3.3 times

Projects that can not only meet current market demands but also address the challenges of the next generation will win the oracle war. While Chainlink is the market leader, there is still much room for improvement in terms of latency and suitability for high-throughput use cases. On the other hand, Pyth’s focus on financial institutions brings a unique dimension to the oracle field but leaves many gaps in cross-use-case universality. Flare combines the above characteristics with the features of L1, making its unique market positioning noteworthy. The winners of this war will be protocols 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 such as artificial intelligence, involving the processing of large and diverse datasets). While it may be too early to draw conclusions now, FLR seems to be underestimated compared to tokens in the same category.

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