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Data Lakes Explained

Comparing Data Lakes and Subgraphs

Comparing Data Lakes and Subgraphs

While there are interesting similarities between Data Lakes and Subgraphs, there are also crucial points of difference. The chief among them being that The Graph offers a decentralized solution, while PARSIQ’s is centralized. Of course, a central tenet of blockchain ethos is decentralization. What benefit is there, then, in providing a centralized solution?

First, there are the issues of speed and efficiency.

Similar to our Data Lakes, The Graph provides platforms with Subgraphs that host elements of data that pertain only to the platform. Yet, in order to do this, their decentralized solution involves coordinating multiple types and sources of data with one another, requiring constant points of connections between, for example, indexers and nodes.

Second, there is the issue of reliability.

Decentralized solutions (like Subgraphs) are not always as reliable as our Data Lakes. For instance, it is up to node verifiers to maintain the efficiency of a Subgraph. The benefit for verifiers is that they earn a profit in the process. But what happens when those verifiers decide to move to another, more lucrative, Subgraph? The consistency and reliability of the data is lost!

Third, there is the issue of customizability.

Unlike Subgraphs, Data Lakes do more than just extract, collect, and process data — as we’ve noted in the previous post in this series, they also offer a high degree of customization! The real payoff of this customization is not just that it makes jobs easier for developers on the back end (and it does do that!); what it also does is allow for a better, more frictionless experience for users on the front end.

Are you or your team ready to get started using Data Lakes?

Check out our docs here: https://network-docs.parsiq.net/

About

PARSIQ is a full-suite data network for building the backend of all Web3 dApps & protocols. The Tsunami API provides blockchain protocols and their clients (e.g. protocol-oriented dApps) with real-time data and historical data querying abilities.

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