SQD incorporates verified blockchain data into Google Cloud BigQuery
SQD has incorporated validated data from 10 blockchain networks into Google Cloud’s BigQuery platform, enabling developers and organizations to access comprehensive chain histories verified through six cryptographic tests.
Summary
- SQD provides indexed blockchain data via Google Cloud Web3 Blockchain Analytics.
- The 10 blockchain datasets include records from each supported network’s genesis block.
- Six cryptographic checks ensure each block’s integrity before the data is uploaded to BigQuery.
- SQD intends to expand with additional networks and tools tailored for AI agents.
SQD integrates validated blockchain data into BigQuery
In an announcement on Aug. 24, SQD revealed that its enterprise division, SQD 360, is delivering the indexing system and data pipelines necessary for the datasets accessible through Google Cloud Web3 Blockchain Analytics.
The initial offering includes 10 networks starting from their genesis blocks, allowing analysts to review their entire available histories instead of just the records collected post-integration. SQD did not specify all 10 chains in its announcement or share a timeline for introducing additional networks.
Before reaching BigQuery, SQD stated that each block undergoes six cryptographic checks. This process involves cross-referencing data from various sources and verifying transaction and state roots—cryptographic values used to confirm that a block’s records align with the underlying blockchain state.
These checks aim to detect any missing, incorrect, or inconsistent records before they are processed in the analytics pipelines. Newly added blocks must also pass through the validation procedure as the datasets continue to refresh.
Once incorporated into BigQuery, the records become accessible through the same cloud environment utilized for business intelligence, machine learning, and extensive data analysis. This setup enables developers to investigate blockchain activity without constructing an indexer, saving an entire chain history, or assembling separate infrastructure for each network.
“Collaborating with Google Cloud Web3 to integrate our validated data standard into BigQuery marks a significant milestone for SQD, signaling that enterprise-grade blockchain data is now available,” said SQD CEO Wanja Oberhof.
The financial specifics, revenue-sharing agreements, or service-level commitments related to the partnership have not been disclosed by either company.
SQD Network distributes storage and query tasks
SQD runs a decentralized data network designed to collect, validate, store, and deliver information produced by blockchains and Web3 applications. This infrastructure distributes tasks among data providers, independent worker nodes, and gateways instead of relying on a single central database.
According to SQD Network documentation, data providers submit blockchain records, which are then assigned to worker nodes by a scheduler. These workers offer storage and computing capabilities, maintain copies of the assigned records, and respond to queries via gateways.
To register on the network, each worker is required to bond 100,000 SQD tokens. They receive token incentives based on criteria such as uptime, data served, and delegated tokens. However, violations of network rules can result in penalties.
Gateways facilitate the connection between data consumers and the worker network. The quantity of SQD held by a gateway operator dictates the volume of requests it can process, linking query capacity to the network’s token-based resource system.
SQD claims its comprehensive data service encompasses over 130 networks, although only 10 are included in the initial Google Cloud contribution outlined in the announcement. Its Portal product provides both historical and real-time information from chains across the Ethereum Virtual Machine, Solana, Substrate, and Bitcoin-based ecosystems.
In contrast to a standard blockchain node, which may deliver raw or recent network data, SQD’s system transforms records into structured datasets comprising blocks, transactions, logs, traces, and changes in blockchain states. These structured records allow analysts to search across extended periods and compare activities without processing raw chain files repeatedly.
Google Cloud broadens access to indexed on-chain records
Google Cloud characterizes Blockchain Analytics as a service that places indexed blockchain data into BigQuery for analysis using SQL, a standard language for searching and organizing databases. This product enables users to query blocks, transactions, event logs, and call traces without needing to operate nodes or create an indexer for each protocol.
BigQuery can also merge on-chain records with a company’s internal data. For instance, a wallet service may compare blockchain transactions with activity logged within its application, while a compliance team could design queries for transfers involving specific addresses. The report’s accuracy would hinge on the query design, address labels, and other user-added data.
Google Cloud began integrating blockchain records into BigQuery in 2018, starting with Bitcoin, and subsequently added Ethereum and various other networks. In 2023, the company included 11 blockchain datasets, featuring Avalanche, Arbitrum, Optimism, Polygon, Polkadot, and Tron.
The SQD partnership follows other initiatives aimed at linking decentralized data sources with cloud services. In July 2025, crypto.news discussed OORT’s dataset listing on Google Cloud Analytics Hub and other enterprise marketplaces. OORT’s offering included 100,000 user-contributed data points, with contributions recorded on-chain to help users verify the information’s source and structure.
Additionally, Google Cloud has developed services that grant applications direct access to blockchain networks. In September 2024, it introduced an Ethereum RPC initially supporting the Ethereum mainnet and test networks, offering a free tier of up to 100 requests per second and one million requests per day.
The RPC service and BigQuery datasets serve distinct purposes. RPC endpoints enable applications to request current blockchain information and submit transactions, while indexed datasets are tailored for searches across vast amounts of historical data.
BigQuery data facilitates enterprise and agent-based analysis
For developers and companies in the U.S. already utilizing Google Cloud, the integration places SQD-provided records within a familiar analytics environment, eliminating the need for a separate blockchain-data system. Google’s documentation indicates users can access public datasets via the Cloud console, command-line tools, or the BigQuery API.
Google covers the storage expenses for datasets included in its Public Dataset Program, while users are charged for the queries they execute. The first one terabyte of query processing each month is free under Google Cloud’s current pricing framework, although access may be restricted by an organization’s own security protocols.
The location of datasets is also significant for U.S. users, with internal policies determining where data is processed. Google guarantees that every public dataset is assigned a specific region, while its BigQuery sample tables reside in a U.S. multi-region. SQD’s announcement did not specify the storage locations for the contributed blockchain datasets.
Agent-based access represents another component of the proposed work. In May, previous coverage indicated that the Solana Foundation and Google Cloud launched Pay.sh, enabling AI agents to pay for APIs using stablecoins, supporting services such as BigQuery, Gemini, and Vertex AI.
According to SQD’s roadmap, additional agent functionalities could allow automated software to retrieve and analyze verified blockchain records within Google Cloud. However, SQD has not clarified which functions will be introduced, which AI systems will support them, or the expected timeline for their availability.
More blockchain networks are also anticipated to be integrated, as indicated in the announcement. SQD has not specified the upcoming chains, disclosed how they will be selected, or provided a timeline for their rollout.


