As blockchain adoption grows, one challenge continues to hold back the next generation of decentralized applications: trustless access to large-scale data. Space and Time is working to solve this by building a decentralized data warehouse that allows developers to query both on-chain and off-chain data while cryptographically verifying the results.
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Powered by its innovative Proof of SQL technology, the platform enables smart contracts, AI systems, and Web3 applications to work with rich datasets without relying on centralized infrastructure. In this interview, we dive into how Space and Time is redefining data infrastructure for Web3 and what it means for the future of decentralized applications.
Brief Overview of Space and Time
The conversation starts off with a brief introduction on what Space and Time does and how it fits into the broader blockchain ecosystem. With 4 years of experience at the company, Catherine has developed a unique perspective on this side of the industry and shares how exciting it is to see the industry mature in this direction.
“We’re data infrastructure for securing, improving data for smart contracts both for DeFi protocols and for institutions who are coming on-chain” - Catherine Daly
Catherine explains that the blockchain is the most secure database in the world. The problem is that data is transparent in general on blockchains and it’s not very scalable. Smart contracts can’t hold a lot of data and they can’t aggregate a lot of data. They also can’t hold historical data or ask questions about that data. So all of these problems create a gap between what’s able to be built on-chain and what exists in traditional markets.
By enabling secure and verifiable data queries, Space and Time helps bridge the gap between traditional financial infrastructure and decentralized networks, opening the door for more sophisticated DeFi applications and institutional participation.
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Pioneers of ZK Proofs For Databases
As blockchain technology continues to evolve, privacy is becoming a bigger topic, especially for institutions exploring on-chain solutions. While transparency is one of the defining strengths of blockchain networks, not every type of data should be fully public. Financial institutions, enterprises, and large organizations often work with sensitive information that needs to remain private while still being verifiable.
Catherine explains that transparency on blockchain is not a flaw. In fact, it is one of its most powerful features. The challenge is that some types of data, like proprietary analytics, financial records, or internal metrics, cannot simply be exposed to the entire network. For many institutions, this creates a barrier to adopting blockchain technology at scale.
This is where Space and Time steps in. The team is pioneering the use of zero knowledge proofs for databases, allowing data to be verified without revealing the underlying information itself. In practice, this means organizations can run queries and analytics on large datasets and prove the results are accurate without exposing sensitive details.
By combining decentralized data infrastructure with cryptographic verification, Space and Time allows smart contracts and applications to work with powerful data tools while still maintaining privacy where it matters. For institutions looking to move parts of their operations on-chain, this kind of balance between transparency and confidentiality could play a key role in making blockchain infrastructure practical for real world use.
What Makes Space and Time Different
Catherine describes Space and Time as having two core functions. The first is bringing data into the ecosystem, which includes indexing and organizing both on chain and off chain information so it can be used by applications. The second is sending data out in a verifiable way, allowing that information to be delivered to smart contracts and other systems with proof that the results are correct.
While many projects focus on one side of this process, Catherine explains that very few are tackling both at scale. Space and Time is not only handling massive amounts of data, it is also proving the accuracy of that data directly inside the database itself.
This is where their technology stands apart from most existing solutions.
By generating zero knowledge proofs for database queries, Space and Time can mathematically verify that the results returned from a query are correct and have not been altered. In simple terms, applications and smart contracts can trust that the data they receive is both accurate and tamperproof without needing to rely on a centralized intermediary.
This capability becomes especially important when it comes to institutions and regulatory compliance. Financial institutions and enterprises often need to demonstrate that their data processes are reliable, auditable, and secure. With cryptographic proofs attached to the data itself, Space and Time allows organizations to show that information has been processed correctly while still maintaining the transparency and integrity that blockchain systems are known for.
By combining large scale data infrastructure with verifiable computation, Space and Time is building a foundation that could allow far more complex applications to operate securely on chain.
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Blockster’s Thoughts
What Space and Time is building goes beyond improving blockchain infrastructure. It challenges how trust is established in digital systems altogether. For years, the tradeoff has been simple. Either you expose your data to prove something is true, or you rely on a third party to validate it for you. Space and Time introduces a third option. Data can remain private while still being provably correct.
From verifying financial credentials without exposing full transaction histories, to proving compliance, identity, or performance metrics across platforms, the ability to work with data that is both private and verifiable opens up a new design space. It can apply to institutional finance, enterprise analytics, marketplaces, creator platforms, and even social or identity systems.
Space and Time’s approach points toward a future where applications do not just process data, they prove it. If that model holds, it could become a foundational layer for the next generation of both Web3 and traditional systems converging into one.
