Parallel’s mission is to innovate and bring DeFi to the next level and to a broader audience. Today we are excited to reveal how Parallel Finance are using SubQuery data in their new application.
“SubQuery is an excellent tool which brought traditional indexing & query technology to Parallel Heiko. The plug-and-play service really saved us a lot time developing our own block indexing tool and maintaining our own solution.” — Parallel Finance
SubQuery’s service helps Parallel Finance store, analyse, and query data on their current Heiko testnet. Some of this data is used directly in Parallel’s new application, helping users understand and analyse DeFi data.
Using SubQuery, you can quickly query account, exchange rates, tokens, transfers, and block data right in SubQuery’s playground.
“We enjoy working with the SubQuery team and the one-to-one customer service they give us. We plan to use it more as we introduce more features into our DeFi application.” — Parallel Finance
In the example below, we’re using SubQuery to show the historical exchange rate for all assets at each and every block.
Parallel Finance is using SubQuery Projects to manage their own project and make updates as required. The indexing and query services we provide are completely managed by SubQuery and provided to the Polkadot community for free in SubQuery’s Explorer.
About Parallel Finance
Parallel Finance is a decentralized money market protocol that offers lending, staking, and borrowing in the Polkadot ecosystem. Similar to the relationship between Polkadot and its “canary network” Kusama, Heiko Finance is the sister network to Parallel, and the parachain that we hope to launch on the Kusama blockchain. We are building for a decentralized future that empowers the community to increase capital efficiency, security, and accessibility through our leverage staking and auction lending platform.
SubQuery is a data aggregation layer that will operate between the layer-1 blockchains (Kusama) and DApps (like Kodadot). This service allows DApp developers to focus on their core use case and front-end, without needing to waste time on building a custom backend for data processing.