The most valuable Web3 and DeFi services need #oracles — but developers face limitations with current solutions ⚠️ Learn how Pyth's low-latency pull oracles uniquely provide: 1️⃣ High-frequency updates 2️⃣ Extensive asset selection 3️⃣ Transparent, trustworthy data sourcing

2/ As you know, many decentralized finance (DeFi) applications need oracles to perform trades, asset valuation, and other transactions which require reference to real-world markets 🌐

3/ Web3 and DeFi developers currently face the following issues with current oracle solutions: 🐌 Data feeds not updating fast enough 💸 Limited, restrictive asset selection 👮‍♀️ Opaque, questionable data quality and origin

4/ 🐌 Price Update Speeds It’s not good to trade at a price from 10 minutes ago versus the price right now Likewise, it’s not good to wait for an oracle to update, say, every 30 minutes. This speed is simply not enough for apps that need very low-latency data

5/ 🔮 Pyth Provides High-Frequency Updates Pyth's prices update more than once a second, ensuring that DeFi apps have recent data and that prices do not deviate too far from trading venues Apps can then offer small spreads and ensure liquidations happen in a timely fashion

6/ 💸 Limited Asset Selection Developers need access to specific markets for their DeFi applications If access to a specific market or asset prices are not available on the chain you’re building on—you’re out of luck

7/ 🔮 Pyth’s 200+ Price Feeds Are Available on More Than 18 Blockchains Pyth’s unique architecture enables it to deliver the same 200+ price feeds to all 18+ Pyth-supported blockchains This makes Pyth an interesting opportunity for teams who want to expand multi-chain

8/ 👮‍♀️ Opaque Data Sourcing There’s a lot of value that depends on oracle prices It’s hard to believe in the accuracy of the prices unless you know where the data is coming from Developers may not want to secure their contracts on data purchased from third-party sources

9/ 🔮 First-Party Data Pyth goes directly to the source of financial market prices, who interact with these prices as their daily business These institutional market players contribute their data directly to the network for transparent, on-chain aggregation for downstream use

10/ Pyth is able to offer these benefits thanks to its pull oracle architecture 🔮 Most oracles use a push model and continuously sends transactions to update an on-chain prices In this model, the oracle can waste gas by submitting price updates that no one will use…

11/ In Pyth’s pull model, users can listen to Pyth’s price feeds update on the Pythnet appchain and “pull” prices from the Pythnet to their native chain when needed Users only pay for the prices they pull. The resulting gas savings enable more frequent, lower latency updates!

12/ Pyth price feeds can update more than once a second on Pythnet—faster than the block time of most chains In this model, applications can always use (”pull”) the most recent Pyth price. In contrast, the push model leaves apps dependent on the last pushed on-chain update

13/ Pyth is also able to scale its entire set of price feeds to a large number of blockchains at once In other words, Pyth does not need to deploy the same feed one by one on every chain 🧠

14/ This is all made possible because price sourcing and aggregation happens on Pythnet, and prices are brought cross-chain through @wormholecrypto Pyth is designed to scale with the growth of Web3 🔮

15/ Join the discussion and explore what Pyth data can do for you:

16/ Building with Pyth is seamless and easy. Explore our documentation below: