Unlocking the Potential of Encrypted Data: Hemera Account Center Index Network Launches新登场

Challenges and Opportunities

Recently, we have observed two significant trends in the blockchain space:

First, with the flourishing development of the blockchain ecosystem and applications, on-chain activities of individual accounts have become increasingly diverse and complex, leaving users with a more comprehensive digital footprint on-chain. Rich on-chain interactions have also brought many new opportunities, such as building on-chain credit scores based on users' asset portfolios and transaction histories. This trend has the potential to drive innovations in traditional financial practices like non-overcollateralized lending protocols.

Second, as the industry matures, project teams are placing greater emphasis on understanding user profiles and assessing user quality when formulating targeted airdrop strategies or analyzing potential user groups. However, they face a significant challenge: EVM accounts are essentially transaction triggers rather than "bank accounts" like in traditional finance. This structural form limits in-depth analysis of account-level data, making it difficult for project teams to gain meaningful insights into their user base.

These trends highlight the urgent need for advanced tools that can effectively analyze and interpret account-level data. To address this need, Hemera Protocol is developing a next-generation account-centric indexing protocol aimed at providing developers with standardized account-level data retrieval and feature development services.

This innovation further extends into an Account-Centric Indexing (ACI) network, ensuring decentralized data management. Utilizing this network, Hemera provides powerful solutions for processing and analyzing blockchain data, facilitating the construction of various user-facing applications suitable for multiple use cases.

What is Account-Level Data Extraction?

When a swap transaction occurs on the blockchain, its raw data does not intuitively present itself as a "transaction." If you directly retrieve this data from a blockchain node, it may appear as a complex array of information that is neither semantic nor easy to analyze, as shown in the blue chart below. Essentially, it records who sent the transaction, where it was sent, and what was input.

The process of data extraction involves transforming this difficult-to-understand data into meaningful semantics. For example, in a transaction, the main information we focus on includes the types and quantities of tokens input and output, as well as the total value of the transaction. Therefore, a typical transaction data extraction might include key elements such as the transaction initiator, bought tokens, sold tokens, their respective quantities, and the transaction amount.

What truly matters is understanding how these transactions affect your overall account status. For instance, a transaction will change your token balance, impact your trading volume, increase your total gas fees paid, and increase your on-chain interaction count.

Hemera encapsulates these account-level changes in a semantic and standardized format, referred to as "features." The red illustration below shows how this swap transaction affects your account status. Through the User Defined Function (UDF) module, developers can design and define these features based on specific needs. This method of data extraction presents complex blockchain data in a more intuitive manner, making development work easier and leading to more meaningful analytical conclusions.

How Do Applications Leverage Hemera Protocol?

The process for applications to utilize Hemera for in-depth account-level analysis is very straightforward. Applications simply query the required features from the ACI network. Hemera provides a range of built-in features, including commonly used metrics such as portfolio balances, trading volumes, collateral lending, and even social data. Developers can easily query any account of interest without needing to write additional code.

Hemera also offers the UDF module to meet developers' more personalized needs. With UDF, developers can create custom features with minimal coding effort. Thanks to the standardized format, these custom features can seamlessly integrate into existing features, facilitating more comprehensive and detailed analysis.

When features are requested, they are transmitted to Hemera's ACI network. Each indexer in the network is responsible for indexing one or more specific features by querying the raw data from the blockchain. The requester then receives semantic account-level data provided by Hemera, avoiding the hassle of directly handling complex raw data.

When functions are requested, they are transmitted to Hemera's ACI network. Each indexer in the network is responsible for indexing one or more specific functions by querying the raw data from the blockchain. The requester then receives semantic account-level data provided by Hemera, avoiding the hassle of directly handling complex raw data.

By leveraging Hemera's ACI network, applications can gain deep insights into account activities and user profiles. This not only helps make more informed decisions within the blockchain ecosystem but also provides a more personalized user experience while simplifying the complexity of handling raw blockchain data.

How Are Features Updated?

Features in the Hemera ecosystem are dynamically updated based on on-chain transactions. Each indexer in the ACI network is responsible for indexing specific features. These indexers operate in real-time, continuously monitoring on-chain transactions related to the features they track.

The simplified workflow begins with developers defining custom features and data classes in the UDF module. Subsequently, indexers capture relevant on-chain transactions, filter the specified data, and pass it to the developers' trigger functions. These functions then process the data to update the account-centric features.

The real-time indexing and updating process ensures the timeliness and accuracy of feature data. By focusing on tracking transactions that affect features, indexers can efficiently handle large volumes of blockchain data and transform it into meaningful account-level information.

How to Create a UDF?

To illustrate the process of building a custom UDF, let's take OpenSea-related features as an example:

1. Feature Definition: Developers first define specific features (such as NFT trading volume, NFT trading collections) and data classes. For example, the "OpenseaOrder" class might include variables such as "orderhash" (string), "offerer" (string), "recipient" (string), and "offer" (dictionary).
2. Trigger and Feature Development: Next, developers create triggers specifying which transactions or log events will change the state of the defined features. This step ensures that the indexers effectively capture relevant on-chain transactions and filter the data of interest. Developers can then write custom logic to update the feature values.
3. Query Execution: Finally, developers run the indexers along with the new UDF and process historical data. The feature data will then be stored in a database, allowing developers to easily retrieve account-level data or query feature values through standard REST APIs.

For a more detailed guide on implementing UDFs, please refer to our documentation: https://docs.thehemera.com

Essentially, each feature is a dynamic entity that is continuously updated based on on-chain activities. The role of UDF is to interpret raw transaction data, create appropriate triggers, and utilize these triggers to maintain the continuous updating of features.

Hemera's Unique Position in Data Analysis

To understand Hemera's unique position in the data space, it can be compared to existing data analysis tools and protocols. The following highlights the main differences:

1. Hemera's core advantage lies in its account-centric data extraction.
2. Dune's Spellbook also emphasizes data extraction, abstracting high-level data patterns from raw data, but it is not account-centric.
3. The Graph, while a popular indexing protocol, is centered around smart contract events. It is well-suited for decoding data related to smart contracts but lacks the ability to extract account-centric data.
4. Debank has the capability to extract account-level data but primarily focuses on DeFi assets, limiting its applicability in diverse on-chain activities (such as on-chain gaming records).
5. Hemera offers unparalleled flexibility in data processing.
6. With Hemera, users can easily access the required data with minimal coding efforts.
7. The Graph allows users to build subgraphs for smart contract data retrieval but restricts deeper data operations.
8. Debank provides a fixed API to query asset information but lacks programmability.
9. Hemera's data updating method is proactive and real-time.
10. Hemera indexers continuously monitor the blockchain and update features in real-time through a "push" mechanism triggered by transactions.
11. In contrast, Dune updates data in a "pull" manner, requiring users to fetch all data from the database to update their own data.
12. In the Web3 application space, Hemera excels in composability and integration.
13. Hemera provides curated data in a standard format, simplifying database construction and maintenance.
14. Dune offers a comprehensive on-chain data query terminal within its platform, but the cost of building standalone applications is high.
15. Debank's fixed API structure limits it to handling only asset-related data.

Looking ahead, as the industry develops and matures, we believe that user profiling will be crucial for user-facing applications. In this evolving environment, Hemera's account-level, multidimensional data will play an indispensable role in enabling more precise and effective user targeting. Furthermore, we foresee an increasing synergy between AI models and on-chain data, with Hemera's semantic extraction capabilities aiding large language models in more efficiently understanding and processing data.

Hemera's vision is clear and straightforward: we are committed to making Hemera a comprehensive data hub for the entire Web3 industry. By significantly lowering the barriers to access and utilization, we will serve a diverse range of users, including developers, researchers, marketing teams, end-users, and AI systems. Hemera's ultimate goal is to become the preferred platform for all users looking to fully harness the value of blockchain data, enabling users in the blockchain ecosystem to easily access important resources and benefit.

Explore Hemera Products:

• Website: https://thehemera.com/

Develop Applications Based on Hemera ACI Network:

• Documentation: https://indexer-docs.thehemera.com/
• Github: GitHub - HemeraProtocol/hemera-indexer at pre-release/v0.3.0

Visit SocialScan Agent Store:

• Website: https://socialscan.io/home

Follow on Twitter:

• Hemera: https://x.com/HemeraProtocol
• SocialScan: https://x.com/socialscan_io