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How blocktorch works
Blocktorch is an end-to-end observability platform built specifically for logs, traces & metrics of web3 applications. Blocktorch is powered by data collectors, data storage and a query engine.
dApps introduce unique data collection challenges due to their decentralized nature:
- Data is dispersed across multiple nodes and platforms, requiring a unified approach to collect and consolidate information.
- Real-time data collection is essential to monitor and react to system changes quickly.
At blocktorch we get the heavy lifting of data collection done for you. Blocktorch's data collection engine is built to be extendible to various data sources. The data we collect is independent of any single RPC Node API, which ensures richer data we can provide and higher speed and reliability.
The architecture of a decentralized application is built out of various layers, and our ultimate goal is to cover all layers, irrespective of the chain you built your dApp on. Today we are supporting ethereum, polygon, BNB chain, optimism, arbitrum and gnosis, base as well as your application frontend through our dragon sdk as data source.
Once data is collected, it needs to be stored efficiently for easy access and analysis. Blocktorch uses a scalable and performant storage system designed to handle the unique requirements of web3 data.
- Blocktorch efficiently scales to accommodate high volumes of data generated by dApps.
- By utilizing time-series databases we store historical and real-time data, enabling efficient querying and analysis.
The query engine is responsible for processing and analyzing the collected data to provide insights and support decision-making.
dApps introduce complexity to the querying process, including:
- Querying data across multiple chains and platforms.
- Handling the unique data structures and formats associated with web3 data.
Blocktorch's query engine is designed to tackle these challenges by:
- Consolidating and contextualizing data from multiple sources, providing a unified view for analysis.
- Supporting complex queries and aggregations on web3-specific data structures, such as smart contract events, function calls, and transaction logs.