A New Era of Data Access in Web3: The Rise of Blockchain Indexers

Data is the core of Blockchain technology and the foundation for developing decentralized applications ( dApp ). While most discussions currently focus on data availability ( DA ), data accessibility is equally important yet often overlooked.

In the era of modular Blockchain, DA solutions have become an indispensable part. These solutions ensure that all participants can access transaction data, thereby enabling real-time verification and maintaining network integrity. However, the functionality of the DA layer resembles that of a billboard rather than a database, meaning that data will not be stored indefinitely but will be cleared over time.

In contrast, data accessibility focuses on the ability to retrieve historical data, which is crucial for developing dApps and conducting Blockchain analysis. Although less discussed, data accessibility is equally important as data availability. Both play different but complementary roles in the Blockchain ecosystem, and a comprehensive data management approach must address both issues simultaneously to support robust and efficient Blockchain applications.

Since its inception, Blockchain has fundamentally changed infrastructure, driving the creation of dApps in areas such as gaming, finance, and social networks. However, building these dApps requires access to a large amount of Blockchain data, which is both difficult and costly.

For dApp developers, one option is to host and run their own archived RPC nodes. These nodes store all historical Blockchain data from the beginning, allowing complete access to the data. However, maintaining archived nodes is costly, and their query capabilities are limited, making it impossible to retrieve data in the format that developers need. While running cheaper nodes is an option, these nodes have limited data retrieval capabilities, which may hinder the operation of the dApp.

Another approach is to use commercial RPC node providers. These providers are responsible for the cost and management of the nodes and provide data through RPC endpoints. Public RPC endpoints are free but have rate limits, which may negatively impact the user experience of dApps. Private RPC endpoints offer better performance by reducing congestion, but even simple data retrieval requires a lot of back-and-forth communication. This makes them request-heavy and inefficient for complex data queries. Additionally, private RPC endpoints are often difficult to scale and lack compatibility across different networks.

Blockchain indexers play a key role in organizing chain data and sending it to databases for easy querying, which is why they are often referred to as "the Google of blockchain." They work by indexing blockchain data and using APIs like GraphQL with a SQL-like query language ( to make it readily available. By providing a unified interface for querying data, indexers allow developers to quickly and accurately retrieve the information they need using a standardized query language, greatly simplifying the process.

Different types of indexers optimize data retrieval in various ways:

1. Full Node Indexer: These indexers run full Blockchain nodes and extract data directly from them, ensuring data completeness and accuracy, but require substantial storage and processing power.

2. Lightweight Indexers: These indexers rely on full nodes to fetch specific data as needed, thereby reducing storage requirements but may increase query time.

3. Dedicated Indexers: These indexers are specifically tailored for certain types of data or specific blockchains, optimizing the retrieval for particular use cases, such as NFT data or DeFi transactions.

4. Aggregator Indexers: These indexers extract data from multiple Blockchains and sources, including off-chain information, providing a unified query interface, which is particularly useful for multi-chain dApps.

It requires 3TB of storage space just for Ethereum, and as the Blockchain continues to grow, the data storage of Erigon archive nodes will also continue to increase. The indexer protocol deploys multiple indexers that can efficiently index and query large amounts of data at high speed, which RPC cannot achieve.

The indexer also allows for complex queries, easy filtering of data based on different criteria, and extracting data for analysis afterwards. Some indexers also allow for the aggregation of data from multiple sources, thereby avoiding the need to deploy multiple APIs in multi-chain dApps. By being distributed across multiple nodes, the indexer provides enhanced security and performance, whereas RPC providers may experience interruptions and downtimes due to their centralized nature.

Overall, compared to RPC node providers, indexers improve the efficiency and reliability of data retrieval, while also reducing the cost of deploying a single node. This makes the Blockchain indexer protocol the preferred choice for dApp developers.

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Building a dApp requires retrieving and reading blockchain data to operate its services. This includes any type of dApp, including DeFi, NFT platforms, games, and even social networks, as these platforms need to read data first in order to execute other transactions.

In the DeFi space, protocols require different information to quote specific prices, rates, fees, etc. The automated market maker ) AMM ( needs price and liquidity information about certain liquidity pools to calculate swap rates, while lending protocols need utilization rates to determine lending rates and liquidation debt ratios. Inputting information into their dApp is essential before calculating the rates executed by users.

GameFi requires rapid indexing and access to data to ensure users can play games smoothly. Only through lightning-fast data retrieval and execution can Web3 games compete with Web2 games in terms of performance, attracting more users. These games need data such as land ownership, in-game token balances, and in-game actions. By using indexers, they can better ensure stable data flows and consistent uptime to provide a perfect gaming experience.

NFT markets and lending platforms require indexed data to access various information, such as NFT metadata, ownership and transfer data, royalty information, etc. Quickly indexing such data can avoid browsing through each NFT one by one to find ownership or NFT attribute data.

Whether it is the DeFi automated market maker )AMM( that requires price and liquidity information, or the SocialFi applications that need to update new user posts, the ability to quickly retrieve data is crucial for the normal operation of dApps. With the help of indexers, they can efficiently and accurately retrieve data, thereby providing a smooth user experience.

In terms of analysis, the indexer provides a method to extract specific data from the raw Blockchain data ), including smart contract events in each Block (. This offers opportunities for more specific data analysis, thereby providing comprehensive insights.

For example, perpetual trading protocols can identify which tokens have high trading volumes and which tokens incur fees, thereby deciding whether to list these tokens as perpetual contracts on their platform. DEX developers can create dashboards for their products to gain insights into which liquidity pools have the highest returns or the strongest liquidity. They can also create public dashboards that allow developers to freely and flexibly query any type of data to be displayed on the charts.

Due to the availability of multiple blockchain indexers, identifying the differences between indexing protocols is crucial to ensure that developers choose the indexer that best fits their needs.

The Graph is the first indexing protocol launched on Ethereum that allows for easy querying of previously hard-to-access transaction data. It uses subgraphs to define and filter subsets of data collected from the Blockchain, such as all transactions related to a certain DEX USDC/ETH pool.

Using index proof, indexers stake the native token GRT for indexing and query services, and delegators can choose to stake their tokens here. Curators can access high-quality subgraphs to help indexers determine which subgraphs to compile data for in order to earn the best query fees. In the process of transitioning to a greater degree of decentralization, The Graph will eventually stop its hosting services and require subgraphs to upgrade to its network, while providing upgraded indexers.

Its infrastructure brings the average cost per million queries to $40, which is much lower than the cost of self-hosted nodes. By using file data sources, it also supports parallel indexing of both on-chain and off-chain data for efficient data retrieval.

The indexing rewards of The Graph have been steadily increasing over the past few quarters. This is partly due to the increase in query volume, but also attributed to the rise in token prices as they plan to integrate AI-assisted queries in the future.

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Subsquid is a peer-to-peer, horizontally scalable decentralized data lake that efficiently aggregates large amounts of on-chain and off-chain data, and is protected through zero-knowledge proofs. As a decentralized worker network, each node is responsible for storing data from a specific block subset, accelerating the data retrieval process by quickly identifying nodes that hold the required data.

Subsquid also supports real-time indexing, allowing for indexing before the block is finalized. It also supports storing data in formats chosen by developers, making it easier to analyze using tools like BigQuery, Parquet, or CSV. Additionally, subgraphs can be deployed on the Subsquid network without migrating to the Squid SDK, enabling no-code deployment.

Despite still being in the testnet phase, Subsquid has achieved impressive statistics, with over 80,000 testnet users and more than 60,000 Squid indexers deployed, as well as over 20,000 verified developers on the network. Recently, on June 3rd, Subsquid launched the mainnet for its data lake.

In addition to indexing, the Subsquid Network data lake can also replace RPC in use cases such as analytics, ZK/TEE co-processors, AI agents, and Oracles.

SubQuery is a decentralized middleware infrastructure network that provides RPC and indexing data services. It initially supported the Polkadot and Substrate networks, and has now expanded to include over 200 chains. Its operation is similar to The Graph using indexing proofs, where indexers index data and provide query requests, while delegators stake shares to the indexers. However, it introduces consumers to submit purchase orders, indicating that the indexers' income is secured, rather than the managers.

It will introduce SubQuery data nodes that support sharding to prevent continuous synchronization of new data between each node, thereby optimizing query efficiency while moving towards greater decentralization. Users can choose to pay a computation fee of about 1 SQT token for every 1000 requests, or set custom fees for indexers through the protocol.

Although SubQuery launched its token earlier this year, the issuance rewards for nodes and delegators have also increased in dollar value month-on-month, which represents a continuous increase in the number of query services offered on its platform. Since the TGE, the total amount of staked SQT has risen from 6 million to 125 million, highlighting the growth of network participation.

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Covalent is a decentralized indexing network, created by block sample producers )BSP( network nodes through bulk export to create copies of blockchain data, and publish proofs on the Covalent L1 Blockchain. This data is then refined by block result producers )BRP( nodes according to established rules, filtering out data that meets the requirements.

Through a unified API, developers can easily extract relevant blockchain data in a consistent request and response format without writing custom complex queries to access the data. The CQT token, which can be settled on Moonbeam, can be used as a means of payment to extract these pre-configured datasets from network operators.

The rewards from Covalent seem to show an overall upward trend from the first quarter of 2023 to the first quarter of 2024, partly due to the rise in the price of Covalent tokens CQT.

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When choosing an indexer, the following aspects need to be considered:

Data Customizability: Some Indexers ) such as Covalent ( are universal indexers that provide standard pre-configured datasets via API. While they may be fast, they do not offer the flexibility that developers need for custom datasets. By using the Indexer framework, it allows for more custom data processing to meet application-specific requirements.

Security: Index data must be secure; otherwise, dApps built on these indexers are also vulnerable to attacks. For example, if transactions and wallets