Subsquid (SQD): A high-quality project undervalued by the market

By David Attermann of M31 Capital

The Subsquid Network is the industry's first modular blockchain data indexing and querying solution, enabling developers to efficiently access and analyze on-chain information. It provides a unique modular and scalable architecture that allows highly customized data processing pipelines and real-time updates. As the market is not well-informed about it, this provides investors with a rare and attractive investment opportunity.

The Current State of Blockchain Data Management

Currently, one of the biggest challenges facing Web3 developers is accessing data at scale. Currently, it is extremely complex to query and aggregate blockchains (transaction and state data), applications (decoding smart contract states), and any related off-chain data (such as price data stored in IPFS and Arweave). This data is often scattered across multiple ecosystems, chains, and technologies, resulting in non-standard structures and data silos, which ultimately make the data set incomplete and difficult to extract meaningful insights.

In Web2, data is stored in centralized data lakes like BigQuery, Snowflake, Apache, and Iceberg for easy access. However, storing Web3 data in similar centralized data lakes would defeat the purpose of open and elastic access. If Web3 application data can be aggregated, filtered, and easily extracted, it will unleash the potential of the industry under the multi-chain paradigm and drive the development of next-generation application capabilities.

Solution:Subsquid network

Subsquid is a decentralized query engine optimized for efficient extraction of large amounts of data. It currently processes historical on-chain data from over 100 EVM and Substrate networks, as well as data from Solana and Starknet, which are in beta. This data includes details such as EVM event logs, transaction receipts, tracking, and state differences for each transaction. It is also developing coprocessors and RAG features that leverage its multi-chain indexing capabilities to connect trustlessly with off-chain data lake resource networks through zero-knowledge proof markets and trusted execution environments (TEEs).

Traditional methods of querying blockchain data are slow, fragmented, and costly, making it difficult for developers to extract meaningful insights. Subsquid's decentralized query engine provides a scalable, modular architecture that allows for custom data pipelines and real-time updates, making data extraction up to 100 times faster and up to 90% cheaper.

Current Product Suite

These tools enable developers to efficiently access and analyze large amounts of blockchain data, making it easier to build and scale complex decentralized applications.

1.Subsquid Network: A distributed query engine that processes historical on-chain data from more than 100 EVM and Substrate networks, as well as Solana and Starknet in beta.

2.Squid SDK: A TypeScript toolkit for building indexers on the Subsquid network, providing high-level libraries for data extraction, transformation, and loading.

3.Subsquid Cloud: A Platform as a Service (PaaS) for deploying Squid SDK indexers, providing Postgres resource configuration, zero-downtime migration, and high-performance RPC endpoints.

4.Subsquid Firehose: An open source lightweight adapter that facilitates the development and deployment of subgraphs without extensive setup.

Modular Architecture

Unlike other solutions on the market, Subsquid's unique modular architecture allows developers optimal flexibility and customization. This will be a key differentiator as we enter the next phase of Web3 development, enabling more sophisticated and feature-rich applications and use cases.

1. Customization: Developers can customize each component of the data processing pipeline to their specific needs, enabling more efficient and effective data processing.

2. Scalability: The modular nature makes it easier to scale out, by simply adding processing nodes to handle increasing data loads.

3. Flexibility: The ability to independently develop and optimize different stages of the pipeline enables Subsquid to adapt to a variety of use cases and performance requirements.

4. Efficiency: With fine-grained control over data flow and processing logic, Subsquid can achieve higher performance and efficiency in indexing and query tasks.

To illustrate the power of a modular approach to data access, we can compare the analytics and real-time data access use cases. Both require an efficient on-chain data source (the Subsquid Network), but the rest of the plumbing requires completely different technologies. In the Web2 world, real-time data access for applications is often powered by relatively small transactional databases (Postgres, SQLite), while analytics requires big data solutions like Snowflake, BigQuery, or Trino. The same distinction applies to Web3 use cases, and Subsquid is uniquely positioned to capture a meaningful share of value from both verticals.

Target Markets and Use Cases

Subsquid’s technology is highly relevant in all areas of the blockchain ecosystem:

1. dApp Projects: Improving the performance and user experience of decentralized applications in DeFi, NFT, Gaming, Social Media, etc.

2. Blockchain Networks: Improving the data infrastructure of L1 and L2 networks to help developers build more efficient data-driven applications.

3. Analytics and Research: Helping companies process large amounts of blockchain data and extract insights and trends.

On-chain and Web3 data is worth orders of magnitude more per byte than Web2 and is consumed by smart contracts, indexers, analytics APIs, and edge technologies such as AI agents.

Customer Case Studies

1.Railgun: Privacy-focused EVM wallet infrastructure

•Railgun used internal tools to call RPC scans directly, but it was slow. After trying The Graph, it was found that it was not functionally consistent across all chains. Subsquid made its new "privacy pool" product faster in balance scanning.

2.CoinList: Leading Token Launch Platform

· Since CoinList frequently handles new projects, it is often troublesome to find node providers for the chains they intend to support. Large providers do not support new, small chains, and relying on small providers can be difficult and unreliable. It is also undesirable to obtain data from the project team itself, as this infrastructure may be tampered with or poorly maintained. Subsquidenables CoinList to bypass this problem completely.

· The platform is very interested in Subsquid’s upcoming native support for hot blocks in the data lake, as this will completely eliminate the RPC constraint. This provides opportunities for defragmentation, not only for token launch platforms such as CoinList, but also for various dApps and multi-chain platforms such as games and social, which may need information from ecosystems of various sizes.

Overlooked and Misunderstood

The main reason why Subsquid is currently undervalued by the market is its lack of visibility. Despite its technical differentiation, functional value, early user traction, and huge potential, the project has not received the attention it deserves. Reasons include:

· Weak brand marketing:Subsquid admits that its initial years were focused solely on product development and customer acquisition, and insufficient investment in brand marketing. To date, its social media influence and marketing activities have not effectively communicated its value proposition to a wider audience.

· Lackluster token launch:Given its unsatisfactory marketing efforts, the launch of the SQD token did not create as much buzz as other blockchain projects, resulting in a lower initial valuation.

· Esoteric Technical Differentiation:The advanced and technical nature of Subsquid’s product may be difficult for the wider market to understand and appreciate.

Now that the team is focused on brand awareness, and with the help of strategic partners such as M31 Capital, we believe the project will be able to better communicate its value to the market, which will drive a significant increase in valuation in the near term.

Competitive Landscape

Subsquid’s main competitors include The Graph, Zettablock, and Space and Time. Each platform has its own unique strengths and weaknesses, and the choice depends on the needs of the specific project. We believe that the Web3 data lake/warehouse market will be huge in the long term, with multiple large winners.

The Graph:

· Predefined Subgraphs: The Graph relies on subgraphs, which are predefined sets of instructions for indexing and querying data. While this approach provides a structured and user-friendly approach, it lacks the deep customization offered by Subsquid's modular processors.

· Indexing Mechanism: The Graph uses a more rigid indexing mechanism, and changes in indexing logic often require major adjustments or redeployment of subgraphs.

· Performance: Provides moderate to high performance depending on the complexity of the subgraph and the network load. It provides low latency for queries and can scale horizontally by adding more indexers.

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Zettablock:

· Centralized Control, Decentralized Intent: ZettaBlock combines centralized infrastructure with decentralized trust mechanisms. This approach provides real-time data indexing and query capabilities, but does not provide the same level of modular customization found in Subsquid.

· Data Pipelines: ZettaBlock focuses on real-time data pipelines with customizable ETL (Extract, Transform, Load) processes, but with a more centralized control framework compared to Subsquid's fully decentralized and modular approach.

· Performance: Designed for real-time data indexing with fast query response times. It is highly scalable and suitable for applications that require real-time data pipelines.

Space and Time:

· SQL Proofs and Hybrid Processing: Space and Time emphasizes data integrity through SQL proofs and supports hybrid transactional and analytical processing. While it provides advanced features for data integrity and processing, its architecture is not as modular or customizable as Subsquid in terms of indexing pipelines.

· Data Warehouse: Space and Time's architecture is centered around a decentralized data warehouse, which, while powerful for large-scale data queries, is more monolithic compared to Subsquid's flexible, modular pipeline.

· Performance: Provides high-performance optimizations for both blockchain and off-chain data. Supports hybrid transactional and analytical processing, ensuring low latency and scalability.

Subsquid’s Differentiation

Subsquid’s unique modular and customizable approach to data processing, coupled with its focus on flexibility, performance, and scalability, makes it stand out among blockchain data indexing and query platforms. This capability will become increasingly valuable as the industry matures and applications become more multi-chain and complex.

1. Customizable Indexers and Processors:

• Flexible Indexing: Allows developers to build highly customizable indexers and processors to facilitate complex data integration tasks and extract meaningful insights from blockchain data.

• Performance optimization: Custom processors can optimize performance, ensuring efficient and scalable indexing and querying.

2. Multi-stage processing pipeline:

• Data flow architecture: Multi-stage processing pipelines separate data extraction, transformation, and storage into independent stages, improving the manageability and scalability of data processing tasks.

• Modularity: Each stage of the pipeline can be developed and optimized independently, providing greater control over the data processing workflow.

3. Support for multiple data sources:

• Diverse blockchain integration: Support for multiple blockchains and the ability to integrate with various databases makes it a versatile tool for developers working in different blockchain ecosystems.

• Adaptability: The platform’s ability to handle multiple data sources ensures that it can adapt to the changing needs of the blockchain industry.

4. Developer-friendly tools and SDK

· Comprehensive SDK: Provides a software development kit (SDK) including tools and libraries that simplify the development of custom data indexers and processors.

· API support: Supports multiple APIs for data querying, including GraphQL and SQL, providing flexibility for developers.

5. Decentralized and scalable architecture

· Decentralized processing: Similar to The Graph and Space and Time, Subsquid utilizes a decentralized network of nodes to process and index data, ensuring high availability and fault tolerance.

· Scalability: The platform is designed to scale horizontally and can efficiently handle increasing amounts of data and queries.

6. Performance and efficiency

· High performance: Through custom optimizations at various stages of the data processing pipeline, Subsquid is able to achieve high performance in data indexing and query tasks. · Resource efficiency: The platform architecture ensures efficient use of computing resources, reducing the cost and complexity of data processing. This last point is particularly important when comparing Subsquid to The Graph, the most established competitor in the space, which operates a highly inefficient network with unsustainable economics. As shown in the chart below, token incentives far exceed network revenue by 50x to 100x per month: Architecturally, The Graph’s “monolithic” index node is a black box that executes subgraphs compiled into WASM. Data comes directly from archive nodes and local IPFS, and processed data is stored in a built-in Postgres database. In contrast, Subsquid Network offers near-zero-cost data access, more granular data retrieval from multiple blocks, and superior batch processing and filtering capabilities.

Relative Valuation

Subsquid's most liquid token is GRT, which trades at an 18x premium to SQD's FDV. Space and Time will be another direct peer token, which should also be a catalyst for SQD when it begins trading later this year, drawing market attention to the value of the Web3 big data space.  

In the long term, as the Web3 industry matures, it is reasonable to compare Subsquid to similar Web2 companies today, which means up to 270x upside if the project (and Web3 as a whole) succeeds.

2030 TAM and Upside Potential

While blockchain data management and Web3 in general are still in their infancy, we can use Web2 as a reference for Subsquid's long-term TAM. I have previously estimated the potential upside for the entire Web3 market by 2030 to be $5.6 trillion in Web3 GDP (total revenue) by 2030. If we take the Web2 Data Lakes and Warehouses market as a percentage of total Web2 GDP, we can apply that to the Web3 GDP forecast and the Web3 Data Lakes and Warehouses market would be $23.6 billion by 2030.

(Source: omnichain Observation, Future Market Insights, Expert Market Research)

If we assume Subsquid has a 20% market share in 2030 and apply a 10x revenue multiple (reasonable for a high growth asset, more on that below), SQD would be valued at $47B, 240x today’s FDV!

Why 20% market share? Looking at the competitive dynamics of Web2 data management providers, market leaders have long maintained 40%+ share. Given the more decentralized nature of Web3, we believe 20% is a reasonable assumption for Subsquid’s upside scenario.

Why 10x revenue? This is the 10-year average for public cloud computing companies (reaching a high of 22x in 2020!).

Subsquid’s 2030 FDV ($B) and sensitivity table for return multiples are as follows:

Investment Thesis

· Highly asymmetric risk/reward investment opportunity; Subsquid’s current FDV offers 18x upside to achieve valuation parity with The Graph (GRT), which we believe has objectively inferior technology and network economics, and long-term upside of 240x+.

· A unique and differentiated asset in a very valuable part of the Web3 technology stack (data lakes and warehouses) that will become even more important as application complexity continues to accelerate, decentralized AI proliferates, and general industry adoption expands, leading to exponential growth in on-chain data.

· Overlooked and severely mispriced due to ineffective brand marketing, lackluster token launch activity, and esoteric technology differentiation.

· Despite the lack of market attention, Subsquid has a superior network architecture to large incumbents, impressive early customer traction, and an exciting roadmap to deliver full data warehouse capabilities as well as co-processing and RAG capabilities.

· Multiple near-term catalysts including mainnet launch in June, upcoming website refresh and rebranding efforts, and a renewed focus on marketing and strategic partner programs.

Technical Design

Subsquid is designed to provide unlimited horizontal scalability, permissionless data access, trust-minimized queries, and low maintenance costs. Its architecture ensures:

· Original data is uploaded to permanent storage by data providers.

· Data is compressed and distributed among network nodes.

· Node operators pay a security deposit that may be slashed due to Byzantine behavior.

· Each node uses DuckDB to efficiently query local data.

· Queries can be verified by submitting signed responses to the on-chain smart contract.

Network Architecture

1.Data Provider: Data providers ensure the quality and timely delivery of data. In the startup phase, Subsquid Labs GmbH is the only data provider, proxying data extracted block by block from each chain. The data is verified by comparing hashes, then split into small compressed blocks and saved to persistent storage. The blocks are randomly distributed to workers.

2.Workers: Contribute storage and computing resources to the network, provide data in a peer-to-peer manner, and receive SQD tokens as compensation. Each worker must register and pledge 100,000 SQD tokens on the chain, and violations of the protocol will be slashed. SQD holders can also delegate tokens to specific workers, indicating their reliability and receiving part of the rewards.

3.Scheduler: Assigns data blocks submitted by data providers to workers. It monitors updates to the dataset and worker set, sends requests to workers to download new blocks or reallocates existing blocks based on capacity and redundancy targets. Upon receiving an update request, the worker downloads the missing data blocks from persistent storage.

4. Log Collector: Collects workers' active ping and query execution logs, batches them and saves them to public persistent storage. These logs are signed by the worker's P2P identity and pinned on IPFS. This data is stored for at least six months and is available to other network participants.

5. Reward Manager: Accesses logs, calculates rewards and submits claimable commitments every cycle. Workers then each claim their rewards, which may expire after a period of time.

6. Data Consumer: Query the network by operating a gateway or using externally provided services (public or private). Each gateway is bound to an on-chain address. The number of requests a gateway can submit is determined by the number of SQD tokens locked, and the longer the lock period, the more virtual "computing units" (CU). All queries cost 1 CU until complex SQL queries are implemented.

Query Validation

The Subsquid network provides the validity of query data through economic guarantees and possible on-chain verification. All query responses are signed by the worker executing the query as a commitment to the response. If it is determined to be incorrect, the worker's bond will be slashed. The verification logic may be dataset specific and include the following options:

1. Proof of Authority: An on-chain identity whitelist determines the validity of the response.

2. Optimistic on-chain verification: After verifying the request, anyone can submit a proof of an incorrect response.

3. Zero-knowledge proof: A zero-knowledge proof verifies that the response exactly matches the request. The proof is generated by a prover off-chain and verified on-chain by a smart contract.

Future Product Development

While we firmly believe that the current indexing and querying capabilities and user appeal of the Subsquid platform are severely underestimated, its long-term growth potential will be driven by upcoming products such as TEE/ZK coprocessing and RAG capabilities, which will become an indispensable infrastructure for future high-performance Web3 applications.

1. TEE/ZK Coprocessor:

• Subsquid is developing a coprocessor solution that combines its powerful multi-chain indexing capabilities with third-party TEE and ZK provers (such as Brevis, Polyhedra, Phala) to enable trustless connection between on-chain smart contracts and their off-chain data lake resource network. Subsquid believes that providing multiple verification options is the ideal way to optimize performance for specific use cases and workloads, rather than developing a single ZK solution.

• This opens the door to high-computation and data-driven on-chain applications such as order book DEXs, lending protocols, and perpetual contracts, even on blockchains with low TPS and strict programming languages.

2. AI Agent/RAG Functionality:

• It is foreseeable that in the next 10 years, most of the Internet traffic will be generated and consumed by AI agents. A contrarian view is that no single ready-to-use AI agent platform may dominate the market, similar to how website building platforms (such as Wordpress) only serve specific hobby niches. Meanwhile, the largest share of post-2000 growth was captured by Amazon Cloud Services (AWS) on the infrastructure side.

• We expect similar dynamics to occur in the AI ​​& Blockchain space. However, the key bottleneck this time may be data access. Subsquid aims to provide a high-throughput minimum viable interface, making data access a growth flywheel.

Customer Attraction and Strategic Partners

Since the testnet launch at the end of last year, the number of users, Squids (cloud indexers) and archive queries (network queries), as well as network data traffic have all shown an upward trend. To compare like with like with The Graph, we need to compare end-user queries. Subsquid end-user queries can be sent from the cloud (which can be tracked) or from a self-hosted solution (which cannot be tracked currently). For Q1 2024, cloud queries totaled 1.2 billion. Since self-hosting achieves approximately 9x more archive queries (archive source distribution graph above), we can assume that self-hosting also sees 9x more end-user queries. Therefore, we can estimate that Subsquid had approximately 10 billion total end-user queries in Q1, significantly more than The Graph, which had 1.6 billion end-user queries in the same period. Google Cloud Partnership (BigQuery Integration) Google Cloud's BigQuery is a powerful enterprise data warehouse solution that allows companies and individuals to store and analyze petabytes of data. Designed for large-scale data analysis, BigQuery supports multi-cloud deployment and provides built-in machine learning capabilities, enabling data scientists to create ML models using simple SQL. BigQuery is also fully integrated with Google’s own business intelligence and external tools, allowing users to run their own code in BigQuery, using Jupyter Notebooks or Apache Zeppelin.

Multi-chain projects can leverage Subsquid combined with BigQuery to quickly analyze their usage across different chains and gain insights into fees, operating costs, and trends. By saving custom-curated data to BigQuery, developers can leverage Google’s analytics tools to understand the usage of their products beyond the context of a single chain or platform.

Roadmap and Upcoming Catalysts

1. Mainnet: Officially launched on June 3, with plans to enhance SQD incentives in July to scale participation.

2.Rebranding: Website refresh and new brand strategy are expected to be launched in the coming weeks.

3.Cosmos Support: Expand the functionality of the Cosmos ecosystem and expand the user base.

4.Permissionless Dataset Submission: Datasets are currently maintained by Subsquid GmbH, with plans for decentralized submission and curation.

5.Decentralized SQL Database Streams: Distribute and synchronize databases in the data lake to ensure accuracy and timeliness.

6. Enterprise Tools: Implement Kafka for real-time data processing and Snowflake for big data analysis and storage.

7. Co-processing and RAG Features: Currently in the PoC stage, the team will release a more specific product roadmap in the near future.

Short-term Revaluation and Long-term Growth Story

SQD is one of the most attractive liquidity token investment opportunities I have ever seen. With multiple upcoming catalysts, we believe the token can re-appreciate 10-20x in the short term, but its long-term TAM provides exciting upside potential of more than 240x. .