Comprehensive Overview of the Seven Leading Web3 Data Tools

Original Article Title: " Seven Major Web3 Next-Generation Data Tools "

Original Source: Biteye

Original Author: Louis Wang

With the development of blockchain technology and the flourishing on-chain ecosystem, abundant interactive behavior has brought about massive data, and data analysis has become an essential part of blockchain applications.

This on-chain data corresponds to the flow of on-chain value, and the analysis of this data and the insights derived from the analysis have become extremely valuable.

Emerging Web3 data products provide rich data visualization capabilities and powerful analysis tools, helping users better leverage the data on the blockchain through functions such as real-time monitoring, data mining, and analysis.

Data Product Classification

From the perspective of the data stack, blockchain data products can be divided into three categories: data sources, data development tools, and data apps.

Among them, data development tools and data apps have the widest audience. Mature data products such as Nansen, Messari, after completing data analysis, package the finished results for users, such as tracking hot projects, on-chain fund flows, etc.

The characteristics of such products are easy to read and understand, low learning curve, plug-and-play. The drawback is the inability to meet customization requirements, belonging to passive research, and often the comprehensive functions are paid.

Highly customizable data development tools, such as Dune Analytics, Flipside, Footprint, are a means of active research.

The characteristics of these tools are freedom and a very high ceiling, completely free to explore, and as high as the sky. However, they require a deep understanding of blockchain data structures, basic mastery of database languages plus some knowledge of smart contracts, with a high learning curve, easy to read but difficult to get started.

Although there are already mature products in the data sub-track, with people constantly expanding the boundaries of blockchain technology, on-chain data is also growing explosively, and users' demand for data analysis is increasing day by day, with a batch of emerging data tools and products appearing in front of users.

The following content of this article introduces seven emerging data products (in alphabetical order):

01 0xScope 

Product Background

Blockchain data is truly transparent, but due to the decentralized production relationship, it has brought about the problem of information fragmentation. The data is scattered, with each piece being valid and usable, but fragmented, making it difficult to generate coherent in-depth analysis from the dispersed data.

At the same time, due to the premise that Ethereum EOA accounts are easily "sybilled," analysis based solely on addresses is one-dimensional and partial. What users want to depict is the operational entity behind the account.

0 xScope addresses these pain points of web3 data by using an invisible hand to pick up blockchain data fragments, making it possible to piece together a complete user profile. The team has proposed an innovative solution: Entity Analysis.

0 xScope has established a weighted aggregation algorithm based on graph computing. By assigning different weights to dozens of different types of rules to identify a user's other addresses, these rules have been continuously tested and refined through deep learning to improve the accuracy of address aggregation. The team reconstructs information units from the perspective of an Entity.

As shown in the figure below, these four seemingly unrelated on-chain addresses were discovered to be the same entity through 0 xScope's aggregation algorithm, meaning that the likelihood that these accounts are controlled by the same person is very high! Through the traces left in different interactions, it is even possible to speculate on the time zone of this person behind the screen, web2 information, and more.

The emergence of the Entity means that the dimension of on-chain analysis is no longer singular. The image of each on-chain entity has become rich and full, and the perspective of analysis is no longer limited to thin EOA addresses. This also means that once someone behaves maliciously, it is no longer possible to escape punishment by simply switching to a new EOA account. The "All-Seeing Eye" will track them to the ends of the earth, leaving no room to hide...

Product Features

The Watcher has just been updated to version 2.0, making adaptive adjustments to the page logic. It consists of three main functional modules:

1. Discovery Module

This part belongs to the data wandering zone, where users can aimlessly browse to see the distribution of whale holdings for various tokens; view the prices and holder changes of various coins according to market capitalization;

Rank projects based on TVL and daily user data to discover hot projects on-chain; or check out the latest blue-chip rankings.

2. DD Module

Wather is very suitable for due diligence. In VC Watch, you can not only view the VC holdings and changes of a specified token to see who has sold and who is still holding, but you can also see the dynamics of each VC, bringing the small leeks and big leeks closer together.

When using Whale Tracking or Wallet Tracking, you can set up alert reminders to easily stay informed of on-chain activities in real time. To avoid data rollback, the delay is approximately 12 Ethereum blocks, within five minutes.

Notable Entity Tracker provides tracking of well-known institutions, market makers, and celebrities, summarizing multiple accounts controlled by a single entity, making trends clear at a glance, with a one-click follow.

3. Research Module

This section should be the part that best represents the technical strength of 0 xScope, focusing on address clustering and visualizing fund flows.

Through the address clustering feature, you can filter out addresses highly related to another address, such as those locking phishing or hacker accounts. You can check if the address is associated with any exchange platform, request the exchange platform's assistance in tracking down the hacker, bringing new hope to recover lost funds.

The fund flow feature visually displays on-chain activities through charts. The chart below shows how the "FTX  Hacker" operated after stealing assets on-chain, converting them to  BNB, and then transferring them elsewhere.

You can also observe the transfer of mask Tokens and, combining it with 0 xScope's tagging system, infer that Jump Trading is a liquidity provider for mask Tokens. Therefore, paying attention to the deposits and withdrawals of these two red addresses is significant for investment decisions.

When assisting in investment decisions, combining Whale Tracking and alert functions can be quite effective. In the Whale Watch feature, you can view the whale size of each Token, enter the corresponding Token whale analysis panel through the Entity Dashboard, and see the whale's latest activities.

Previously, someone used this method, observed a large amount of whale withdrawals in YFII, identified the whale with the most accumulation behavior and price correlation, set up alerts to track operations, and ultimately gained a 700% profit by using the whale hunting strategy. For specific steps, please refer to this tweet.

One-Sentence Summary

The Watcher tool by 0xscope has powerful technical innovation. Through entity analysis and address clustering, it can help users unravel relationships in complex on-chain addresses and on-chain behavior, making it particularly useful for due diligence. It can also visualize the flow of funds for a token, set up alerts for tracking targets, engage in watch-to-earn activities, and transform smart asses into smart money.

02 Arkham

Product Background

Arkham is a data analysis app that focuses on address clustering and tracking. The product is active in on-chain tracking and analysis of various hot events, such as the FTX exploit and the November CRV shorting, attracting widespread attention.

The product is currently in a closed beta phase, and users can apply for beta testing slots on the official website.

Product Features

1. Asset Information

Upon connecting a wallet, users can view their asset information, which is essentially a simplified version of Arkham's dashboard. It includes asset tables, historical asset levels, asset portfolios, and transaction records. Real-time 24-hour asset changes are also displayed for held assets.

2. Data Tracking Dashboard

The Dashboard is Arkham's main feature, and it is easy to create. No programming is required; users only need to input and select conditions to generate outputs, with high speed. This feature can be entity analysis-oriented or token analysis-oriented.

Arkham has collected the addresses of mainstream market makers, clustered them into entities for easy user queries. As an example of entity analysis, in the following image, I have created a dashboard comparing different market makers. The dashboard includes assets, asset compositions, asset historical curves, and recent operations of four market makers: Wintermute, Jump Trading, Alameda, and Jane Street.

You can see how powerful the liquidity provider is holding what token, operating what token, and thus providing guidance on following or avoiding.

Taking Token analysis as an example, looking at the November AAVE borrowing $CRV short event, by selecting the filter condition to choose a large amount of CRV deposited in OKX Token , you can see that it is all Eisenberg (the one who borrowed crv short this time and previously attacked, causing Mango to lose one billion) in the output.

Subsequently, $CRV underwent a squeeze and short squeeze in AAVE, with AAVE's position being liquidated. By selecting CRV sent to AAVE in the board conditions, it is shown that due to insufficient liquidity, the liquidated position was too large, and the entire liquidation process lasted for 40 minutes, ultimately leaving AAVE with a seven-figure bad debt.

3. Visualizer

The visualizer is a tool that visualizes the connections of on-chain addresses. Similarly, by entering an address or entity name, a graph can be automatically generated. For example, if I want to track the initial distribution of APEcoin, as shown in the figure below, the top part is the airdrop address, the middle part is the foundation wallet managed by Coinbase, and the bottom part is some untagged addresses.

One-Sentence Summary

Arkham's simple and easy-to-use on-chain data tracking app that can create information-rich dashboards with flexible filtering conditions, whether for entity-oriented analysis or Token and protocol analysis, is flexible and easy to use.

The current product is still in internal testing, and more features such as large transaction alerts are in development.

03 Chaineye 

Product Background

With the growing Web3 ecosystem, there are various projects emerging in each track with its own characteristics. A rich ecosystem is certainly a good thing for users, but it can also cause some confusion. Which one is better after all, or what choices are available for me to choose from?

After all, not every ordinary user has the time and energy to research each project. Chaineye is a data product that assists users in daily decision-making. It aims to start from a practical perspective, play the role of an aggregator, and address issues such as choosing more frictionless multi-currency cross-chain solutions.

Product Features

1. Asset Cross-chain Aggregation

The multi-chain landscape brings blockchain ecosystem diversity but also leads to the issue of liquidity fragmentation.

With different bridges supporting specific cross-chain transfers, it is difficult for users to understand the differences, causing user confusion to some extent.

Chaineye aggregates information on various asset cross-chain transfers, displays real-time cross-chain options based on user preferences, including transfer time and fees. Users can easily select the most suitable option and directly connect to the cross-chain bridge, making the process very convenient.

2. Centralized Exchange Platform Token Deposit/Withdrawal

If users are concerned about the security of decentralized cross-chain bridges, they can also utilize centralized exchange platforms for asset cross-chain deposits and withdrawals. The CEX Transfer Fee feature supports over a hundred commonly used tokens and mainstream exchanges, listing the deposit/withdrawal details for each chain, asset, and exchange platform. Users can choose the most suitable method based on their needs.

3. Stablecoin Dashboard

For mainstream stablecoins in the market, Chaineye provides the most comprehensive comparison dashboard. It includes the total market value of stablecoins, the issuers of various stablecoins, the chains they operate on, whether there have been any unpegging incidents, the collateral composition of the stablecoins, whether they have undergone audits, and detailed audit reports.

It also distinguishes between native stablecoins and non-native stablecoins (such as BUSD on Ethereum and Binance-Peg BUSD on the BNB chain), helping everyone to have a deeper understanding of the risks associated with stablecoins and avoid being flooded with FUD noise every day.

4. ETH 2.0 Staking Yield Comparison

After Ethereum's official transition to PoS, ETH 2.0 staking has become a popular financial choice for many. Especially with Vitalik Buterin's recent announcement that the Shanghai upgrade of Ethereum is expected to take place in early 2023, allowing staked ETH to be withdrawn, ETH 2.0 staking will no longer be a "locked-in" investment. How can retail investors choose a staking service provider to maximize their returns?

Chaineye aggregates and compares information on mainstream staking service providers' staking rewards, scale, withdrawal/redemption criteria, etc. By entering the estimated amount of ETH to stake, users can get a rough estimate of the return, making it very convenient.

5. RPC List

If you want to avoid IP monitoring by Infura, Chaineye also provides an RPC List. Users can choose alternative RPCs based on latency and provider.

One-sentence Summary

In short, Chaineye is an information aggregator focusing on hot topics such as stablecoins, cross-chain, etc., providing users with the most comprehensive information comparison to save time and enhance user experience.

04 EigenPhi

Product Background

As research on MEV gradually becomes mainstream, more and more people are starting to pay attention to this corner of the dark forest.

EigenPhi is a research platform for MEV data in DeFi, with a focus on identifying and tracking on-chain MEV extraction, such as arbitrage, sandwich attacks, liquidations, etc. It not only showcases the MEV market but also provides detailed information on each MEV transaction for reference.

Product Features

On the Overview page, EigenPhi can inform you about the actual transaction volume and profit (gross profit - miner fee) of various types of MEV, their respective proportions, and growth trends. This can give users a comprehensive current overview of the MEV market.

By observing the transaction volume and revenue of various types of MEV, it can be seen that the overall revenue of arbitrage accounts for about one percent of the arbitrage transaction volume, while sandwich attacks account for about one-thousandth.

Currently, in terms of transaction volume, sandwich attacks are the most common, accounting for over 80% of the total MEV transaction volume. However, when ranked by profit, arbitrage revenue contributes to over half of the actual MEV market revenue.

In other words, sandwich attacks, which we consider to be harmful MEV affecting user experience, dominate the entire MEV market. However, the actual revenue they generate is not as significant as the good MEV revenue from arbitrage, which promotes market price stability.

The MEV Live-Stream is a very interesting feature, similar to watching the constantly changing stock market index in the past. It will actively monitor and capture the latest MEV-related transactions and broadcast them on this scrolling panel in real time.

Users can clearly see data such as the type of MEV involved in the transaction, the contract address initiating the MEV transaction, actual revenue, costs, and more related to that transaction platform.

Interestingly, it is often possible to see some transactions with almost zero or negative revenue, such as failed arbitrage or very low-profit sandwich attacks.

For friends who are not familiar with MEV or feel that the MEV technology threshold is too high and hesitate to proceed, they may as well take a look at this panel, and they will be glad that they have avoided one way of losing money.

Of course, there are also many skilled MEV players. Looking at the leaderboard, interestingly, the MEV income on BSC is much higher than on Ethereum. The player ranked first on BSC has harvested $567k with a cost of $587, with an investment return ratio as high as 90000%, making it out of reach for others.

On the other hand, the top earner on ETH made $41k with a cost of $103k, with an investment return ratio of only 39.7%; half of the top earners on Ethereum MEV profit from sandwich attacks, while the other half comes from arbitrage. The investment return ratio of arbitrage is often higher, while the profit from sandwich attacks is relatively small with high costs.

Users can view details according to the MEV profit method, such as viewing the transaction distribution of sandwich attacks, with UniswapV3 being the hardest hit, accounting for over half. Users can also see when the most recent attack occurred, the tokens involved, and the profit situation.

In EigenPhi, every MEV transaction clearly shows the entire operation behavior and logic, simplifying and revealing details such as the complex interaction process, transaction costs, profits, etc., making it easier for users to understand.

Sharing an interesting arbitrage case: The arbitrage contract (0x8) borrowed 90 ETH from DYDX flash loan, purchased #1633 BAYC, and simultaneously obtained 10,000 Ape staked under that NFT. After exchanging the Ape for 32.68 ETH, the NFT was sold for 65 ETH, resulting in a profit of 4 ETH. The record in EigenPhi is shown in the image below:

The current MEV section of EigenPhi's data supports Ethereum and BSC chains in part. In addition to MEV, EigenPhi also provides liquidity pool distribution monitoring, pinpointing which pool of which protocol has the highest trading volume;

Malicious Token recognition feature. Malicious Token refers to a token that charges a transfer fee or transaction fee without notifying the user, helping users mitigate risks.

Additionally, EigenPhi also has a Research section, providing their latest research reports, which are worth reading.

One-sentence Summary

EigenPhi is a data analysis platform focused on the MEV market, able to identify, track various types of MEV, analyze the MEV market with visual charts, and break down each transaction.

It provides data for MEV research for researchers and offers insights and references for MEV enthusiasts.

05 GeniiData 

Product Background

GeniiData is positioned as a data analysis platform focusing on cross-chain data analysis and an API factory, emphasizing high performance, high data reliability, and broad coverage.

It provides professional tools for individual data studios to discover, validate, and build Web3 through blockchain analysis. For enterprises, GeniiData is an incubator for decentralized applications, providing access to comprehensive on-chain data APIs.

GeniiData is a community-driven open platform that allows users to share complex data insights and collaborate on applications in the Web3 ecosystem.

Product Features

1. High-granularity multi-chain parsing + powerful cross-chain analysis function + excellent user experience

GeniiData currently parses over a dozen chains, including BTC (most data platforms do not have BTC data) and some new public chains, layer 2, such as Aptos, StarkNet. Analyzing more chains brings richer analytical content.

With the development of blockchain, a new trend of multi-chain parallelism will emerge. Many giant protocols such as Uniswap, Aave, etc., will be cross-chain deployed. Even Aave V3 has new features for cross-chain access, so analyzing protocols on a single chain will increasingly appear one-sided.

GeniiData provides powerful cross-chain analysis capabilities, allowing users to aggregate and compare data from various chains, gaining more comprehensive and higher-dimensional insights.

When it comes to user experience in creating data query dashboards, GeniiData stands out as one of the best on the market, with clean pages, clear logical structure, and many commonly used abstract tables. For example, various standard tokens are abstracted and classified into balance tables, providing great convenience for queries.

2. Smart Contract Automatic Decoding Feature

In most data analysis platforms, parsing the smart contract of a project is often labor-intensive, requiring submission of an application, manual review by staff, and then manual parsing, which can take 2-3 days if fast or one to two weeks if slow.

GeniiData offers a smart contract automatic decoding feature without the need for verification. After submitting the contract, decoding can be completed within a few hours. This is very helpful for focused project research, as it provides complete event data after decoding, making analysis more convenient.

3. Data Product Driver

The API marketplace of data platforms is becoming increasingly competitive. GeniiData plans to build an API factory, considering both the historical integrity and timeliness of data queries, becoming a driver for Web3 data products, providing stable and efficient services through easily built APIs to support toC business traffic.

At the same time, GeniiData also supports machine learning to train on-chain data, using artificial intelligence to explore a new paradigm of Web3.

One-sentence Summary

GeniiData is industry-leading in interpreting chain diversity, historical data integrity, and user experience. The innovative smart contract automatic parsing feature improves research efficiency, and the API factory empowers data products.

06 MetaDock 

Product Background

Unlike other data platform products, MetaDock works as a browser extension, aiming to optimize users' experience with blockchain explorers.

Product Features

1. Aggregates various EVM blockchain explorers, eliminating the need to search for a blockchain explorer separately; users can directly query within the plugin, but it only supports some EVM chains.

2. As a web plugin, when linking to a blockchain explorer, it adds some tagging features, such as indicating low/high-risk accounts and providing hyperlinks to commonly used tools like DeBank.

3. Fund Flow. By clicking on the Fund Flow tab, users can visually see a flowchart of the queried account's associated accounts and fund flow. Through the top-right filter, users can choose to display specific transfer addresses/entities or currencies.

One-sentence Summary

MetaDock is a Chrome extension designed to enhance user experience with blockchain explorers. On one hand, it aggregates multiple EVM-compatible blockchain explorers and adds address tagging;

on the other hand, it provides fund flow tracking, making it a practical tool.

07 Zettablock 

Product Background

ZettaBlock is an enterprise-grade full-stack Web3 infrastructure for indexing and analysis, connecting on-chain and off-chain data.

ZettaBlock is mainly targeted at enterprise teams and developers, who can rapidly build real-time, public-facing, reliable GraphQL APIs through the platform built on ZettaBlock using SQL.

Applications built on ZettaBlock only need to interact with a few general and user-friendly APIs, which provide efficient access to a large number of disparate data sources; developers can easily customize APIs to fit their own business logic.

Custom API is a GraphQL API endpoint where users can write full SQL queries, making it easy to build through ZettaBlock's API Builder. The customized GraphQL API is real-time (100ms latency), cost-effective (1000 times cheaper than the Analytics API), and can handle high QPS, making it ideal for providing API support for consumer-facing dApps.

Data Lake API

The Data Lake API is an analytics API for interacting with ZettaBlock's data lake. Users can use it to submit arbitrary SQL queries to the data lake and receive the results accordingly. For large results, streaming mode access and file writing are also available.

Pre-built API

The Pre-built API is a collection of GraphQL APIs co-built by the ZettaBlock team and the community. Pre-built APIs are designed to meet common query and metric needs, similar to Dune's Spellbook, to avoid reinventing the wheel.

3. On-chain Data + Off-chain Data

When conducting data analysis, a common issue is the disconnect between on-chain and off-chain data, making it difficult to integrate them for comprehensive analysis. ZettaBlock has made a breakthrough in this area by supporting the aggregation of off-chain data, partly through community contributions.

For example, data from the Polygon team's protocol_mappings table, on one hand, and from some well-known data sources like CoinGecko (e.g., prices.usd table), on the other hand.

At the same time, various teams and analysts can upload data to their separate data lakes within ZettaBlock, facilitating the combination of on-chain and off-chain data for more thorough analysis without compromising data privacy.

In the future, ZettaBlock will also introduce an API marketplace, allowing developers to benefit from it. The basic process will be as follows: Developers use the datasets provided by ZettaBlock to query using SQL, for example, "How many addresses hold BYAC for over a year and actively bought this NFT," and after the query is complete, an API is automatically generated using the API Builder and placed in ZettaBlock's API marketplace.

Another user interested in this query can directly use the API and pay for it, with the creator automatically receiving a commission, enabling individual developers to monetize their innovative ideas and knowledge.

One-Sentence Summary

ZettaBlock is a full-stack real-time web3 data infrastructure for indexing, analyzing, and connecting on-chain and off-chain data, allowing developers to easily build real-time, reliable, data-intensive applications as the foundation of data-class products.

08 Seven Data-Class Products Summary

Discussion

From the above introduction, it is not difficult to find that the development of emerging data-class products mainly revolves around three functions:

Entity Identification

Capital Flow

API

Entities abstract multiple associated addresses together, which is very helpful for improving data analysis quality and is much more valuable than analyzing single addresses.

In addition to addresses disclosed by institutions, exchanges, and other public sources, more hidden addresses rely on data platforms to explore them on their own. This depends largely on each platform's capabilities. The depth of exploration through their respective algorithms and the breadth of entity identification are competitive points.

Obviously, each platform's address aggregation and entity identification will have some discrepancies. This can also confuse users, making it impossible to compare and verify data, seemingly only able to choose to believe "blindly."

In fact, it is true. Only a fuzzy correctness can be obtained. Borrowing Kofi's words, it is difficult to say which data is correct.

Visualizing capital flow facilitates investment analysis for investors, especially when combined with entity identification and address aggregation features. It can basically analyze addresses worth tracking and then issue warnings.

The API service of data analysis platforms is another major competitive point, all vying to be the API factory. With users' increasing demand for on-chain data, more data-class DApps and tools will emerge. The flexible nature of APIs is very suitable for these DApps to be built on the foundation of data analysis platforms, further enabling data analysis platforms to play the role of infrastructure and absorb the traffic brought by data products.

The relationship between emerging data products and existing products is complementary and competitive. On the one hand, due to market growth, existing products do not have enough coverage, so new products fill the gaps in new sub-tracks. On the other hand, if new products and existing products are in the same track, their competition mainly revolves around the following aspects:

Technology. Whether the new product has more advanced technology, such as faster data processing capabilities, more powerful analytical functions, simpler development interfaces, etc. These advantages can make the new product more competitive, attracting user adoption;

Market Share. Existing products may already have a certain market share, with a larger user and customer base, forming a stable revenue model; how a new product opens up the market through distinctive features, better user experience, and more aggressive marketing is key to the success of the product;

Brand Effect. Existing products may have already established a good brand reputation, with high brand awareness and reputation. These advantages can make existing products more easily favored by users and attract attention, bringing about network effects.

The importance of on-chain data comes from the gradual maturity of blockchain technology and its vigorous application. Flexible use, combined with various data products, will provide us with a fresh perspective in the crypto world.

Through the analysis of on-chain data, users can obtain more comprehensive and accurate information, assisting in research or investment; through on-chain transparent and truthful data, users can also use it as a guiding light in the dark forest, illuminating the path ahead and protecting themselves.

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