SQD says it is bringing validated blockchain data from 10 networks into Google Cloud BigQuery, with each block passing six cryptographic checks before it lands in the warehouse.
- 10 blockchain networks added to BigQuery, according to SQD
- Six cryptographic checks per block
- Genesis-to-current history for the initial set
- Enterprise analytics, compliance, and machine learning are the target use cases
The company said the integration was announced on Aug. 24 through its enterprise arm, SQD 360. The pitch is simple: don’t just index blockchain data, validate it first, then hand it to analysts inside a familiar SQL warehouse instead of making them babysit nodes and duct-tape their own infrastructure together.
That distinction matters. Indexed data is organized for searching and querying. Validated data is organized and checked against the chain’s cryptographic fingerprints, which is the part enterprises tend to care about when bad data can turn into bad reports, broken models, or compliance headaches.
SQD says the initial batch reaches back to each network’s genesis block, so users get full chain history rather than a partial snapshot. It also says fresh blocks keep passing validation as the datasets update, which is the only way this setup is useful beyond a flashy demo.
According to SQD, each block goes through six cryptographic checks before delivery. The company says those checks are meant to catch missing, incorrect, or inconsistent records. In practice, that means comparing data from multiple sources and checking values such as transaction roots and state roots, the blockchain’s own cryptographic summaries that should line up if the data is legitimate.
That is the core sell: not trust me, bro indexing, but data that has been checked before it hits BigQuery. In a sector where plenty of dashboards are dressed up like authority and operate like guesswork, that is a welcome upgrade.
Wanja Oberhof, SQD’s CEO, framed the move as a milestone for both the company and the broader market:
“Partnering with Google Cloud Web3 to bring our validated data standard to BigQuery is a defining step for SQD, and a strong signal that enterprise-grade blockchain data has arrived, ”, Wanja Oberhof, SQD CEO
There is some substance behind the corporate cheerleading. Google Cloud has been building blockchain analytics support for years, and Public Blockchain Datasets Available in BigQuery already hosts blockchain datasets for Bitcoin and a growing list of other networks. Google Cloud’s Supported Datasets for Blockchain Analytics include Google-maintained and community-maintained blockchain data, with networks such as Arbitrum, Avalanche, Cronos, Ethereum, Fantom, Optimism, Polygon, Tron, and more.
So this is not Google “discovering” blockchain data. It is Google continuing to formalize it, while SQD tries to wedge itself in as the cleaner pipe.
That is a sensible angle. The boring parts of crypto infrastructure are often the real bottlenecks: data reliability, query performance, operational overhead, and the eternal joy of explaining to a compliance team why two feeds disagree. If SQD’s validation model is solid, it removes a chunk of friction for firms that want blockchain data without building and maintaining their own indexers.
Still, the announcement leaves some important blanks. SQD did not disclose the exact 10 networks, financial terms, revenue-sharing arrangements, service-level commitments, or a timetable for the next batch of chains. It also did not say where each dataset is stored regionally, which AI systems will eventually support agent functions, or how those future features will work in practice.
Those details are not minor footnotes. In enterprise crypto, the shiny part gets the headline, but the commercial terms, latency, storage location, and support commitments are where the actual deal lives. That is where the bill hides, too.
Google Cloud’s public dataset model also matters here. BigQuery users can reach public datasets through the Cloud console, command-line tools, and the BigQuery API. Google covers storage costs for datasets in its Public Dataset Program, while users pay for the queries they run. Under current pricing, the first terabyte of query processing each month is free, which is generous enough for experimentation and small workloads, though serious analytics still come with a bill.
SQD says its broader data service covers more than 130 networks, and its Portal product offers historical and real-time information from ecosystems including Ethereum Virtual Machine chains, Solana, Substrate, and Bitcoin-based ecosystems. That breadth is part of the company’s pitch: one pipeline, many chains, less plumbing for users who just want the data.
There is also a decentralization angle that is easy to miss if all you see is the BigQuery logo. SQD says workers on its network must bond 100, 000 SQD tokens to register, with rewards based on uptime, data served, and delegated tokens. Provable violations can lead to penalties, and gateway query capacity depends on how much SQD is locked by the operator.
In theory, that creates incentives for honest service. In practice, tokenized infrastructure only works if the economics are tight and the enforcement is real. Otherwise you end up with the usual blockchain theater: slick branding, fuzzy accountability, and a lot of people pretending incentives are the same thing as reliability.
The AI angle is the other obvious hook, though it is still more promise than product. SQD has signaled future agent-based features, meaning automated software systems that can retrieve and analyze data without a human manually clicking every query. That direction makes sense: if AI agents are going to operate onchain or make decisions from onchain data, they need inputs that are not just available, but dependable.
A model fed bad chain data does not become “intelligent.” It just becomes a faster way to be wrong.
For enterprises, the real question is whether validation meaningfully reduces the need for separate infrastructure while still meeting expectations for freshness, completeness, and uptime. Validation helps, but it does not magically erase latency issues, chain reorganizations, or the odd edge case that makes blockchain data work far less glamorous than the pitch deck suggests.
Google Cloud’s existing footprint also makes one thing clear: SQD is entering an established ecosystem, not a blank slate. Google has already spent years building blockchain datasets and related tooling, including an Ethereum RPC service launched in September 2024. That means the market for blockchain data inside Google Cloud is already real, and competitive.
The practical upside of SQD’s move is easy to grasp. If the validation holds up, data teams can work inside BigQuery with stronger trust in what they are querying. Compliance teams get a cleaner foundation. Analysts get fewer weird surprises. Machine-learning pipelines get less garbage upstream. That does not solve every problem, but it knocks out a painful one.
The skeptical view is just as important. “Validated” sounds great, but the usefulness of any dataset still depends on what exactly is being checked, how fast it updates, what it covers, and whether the user can verify it against their own internal records. Without the chain list, the storage details, and the commercial terms, a lot of the interesting stuff is still behind the curtain.
Key questions and takeaways
-
What does SQD say it is adding to BigQuery?
SQD says it is adding validated onchain data from 10 blockchain networks into Google Cloud BigQuery through SQD adds validated onchain data to Google Cloud BigQuery. -
What does “validated” mean here?
SQD says each block passes six cryptographic checks, including comparisons across multiple sources and checks of transaction roots and state roots. -
Why not just use indexed blockchain data?
Indexed data is organized, but validation adds a check that the records match the chain’s cryptographic state. That extra layer matters when accuracy, compliance, and reporting are on the line. -
What is still unclear?
SQD has not disclosed the exact 10 networks, financial terms, revenue-sharing arrangements, service-level commitments, regional storage details, or the roadmap for future AI-agent features. -
Is Google new to blockchain analytics?
No. Google Cloud already supports blockchain datasets in BigQuery, so SQD is plugging into an existing system rather than opening a brand-new market. -
Does validation solve every blockchain data problem?
No. It improves trust and correctness, but it does not automatically guarantee perfect freshness, full completeness, or immunity from chain-specific edge cases.
The bigger takeaway is that blockchain data is moving beyond raw indexing and toward something more serious for enterprise use. That is good for analysts, good for compliance, and good for anyone who is tired of pretending that every chain feed is equally clean. In crypto, trust is earned the hard way, one cryptographic check at a time.
Further reading
For a wider view on blockchain data infrastructure, analytics, and the compliance angle that keeps boring people rich:
- SQD adds validated onchain data to Google Cloud BigQuery
- Google Cloud adds 11 more blockchains to BigQuery public datasets
- SQD’s complete data stack
- Top 5 blockchain analytics trends for 2025: DeFi, compliance, AI, and privacy
- Kenya seeks blockchain analytics to police new crypto regime
- Singapore stops $7M in crypto scam losses with blockchain tracing
