Case Study: How Hydration uses SQD Data Access to facilitate its DeFi success

Fact Sheet

Quick description of Hydration: Hydration is a scalable appchain on Polkadot that provides a cross-chain liquidity protocol serving as a local hub for DeFi. It unites swaps, lending, and a native stablecoin as part of its platform. 

Chains served: Polkadot and its parachain ecosystem. 

Make or break feature: Substrate indexing, and  quick response times. 

Using SQD for: indexing all of the data displayed in the dApps’ frontend, especially user-facing information such as balances, transactions, and statistics. 

Only possible with SQD: scalable, fast, and efficient Substrate indexing 

How SQD’s data access supports Hydrations’ growth 

Hydration, formerly known as HydraDX, is the leading DeFi protocol in the Polkadot ecosystem. While an ecosystem of appchains all connected to the relay chain offers benefits such as customization and shared security, it can create challenges when it comes to obtaining data. As a DeFi protocol, Hydration provides different liquidity pools to allow users to swap and trade across appchains. The automated router ensures that traders will be routed through the most efficient path, reducing slippage and price impact. 

Hydration requires onchain data for each user interaction. Whenever a user connects with their wallet, they are shown their trading history, assets, and balances. To enable that, the Hydration team was looking for a performant, scalable indexer that could provide nearly instant access to onchain data without sacrificing Web3 values such as permisisonlessness. Additionally, just in case they would run into challenges, they also value fast response time. 

“We were looking for a performant indexer. Besides the good tech, the response time of the SQD team has been a big factor.”

While Hydration initially relied on a different indexer, since their migration, “they haven’t looked back” and are very satisfied with the speed and the performance. 

“Indexers are key to any web3 solution since querying archive RPC separately for each request is really inefficient. Having an efficient data layer has absolutely boosted our performance. When FireSquid was released, we improved our processing performance by orders of magnitude.”

Working together 

The team at Hydration described working with the SQD Labs team as absolutely great. The team was always there to help with any issues.”