We’ll be exploring how components such as record keeping (storage) and smart contracts (computation) can be moved off-chain to enable more robust computations and storage requirements without sacrificing security and scalability requirements..

Lakehouses can help address several major challenges with data warehouses, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support.

Data mesh is a new paradigm for building the next-generation data platform, and founded in four principles: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a platform, and federated computational governance.

To help data teams stay on top of the changes happening in the industry, we’re publishing in this post an updated set of data infrastructure architectures. They show the current best-in-class stack across both analytic and operational systems, as gathered from numerous operators we spoke with over the last year. Each architectural blueprint includes a summary of what’s changed since the prior version.

Financial composability is not the only form of composability. There’s an even larger opportunity for composability: data composability. All ledgers—asset ledgers must achieve Composability — As more data, state, and functions are added to a decentralized ledger, they increase the breadth and depth of the substrate on top of which new applications can be built. Composability is the ultimate network effect.

We believe that SQL has become the universal interface for data analysis.Like networking we have a complex stack, with infrastructure on the bottom and applications on top.What we need is an interface that allows pieces of this stack to communicate with one another. Ideally something already standardized in the industry. Something that would allow us to swap in/out various layers with minimal friction.That is the power of SQL. Like IP, SQL is a universal interface.