GraphQL On L3 Atom

What is GraphQL?

What this Looks Like on L3 Atom

Plans for the Future

  • Filtering: Letting users query data from a specific time frame, at specific intervals, from specific exchanges, e.t.c.
  • Indexing: Letting users search for specific order IDs or block numbers, for example
  • Custom Functions: Developing custom functions that users can then use in their queries to have massive control over the data they receive. This can include averages, totals, minimums, maximums, metrics, e.t.c. This is an area that we can have a lot of fun with, and where we’ll probably be spending most of our development time
  • Multiple Schemas: We didn’t touch on this much in this article, but one of GraphQL’s biggest feats is its type system, which lets custom schemas be developed that can all link to each other. E.g., One schema of type Block might have, as a part of it, an array of Transactions , which could be another type. The way that these types all point to and contain each other is where the name comes from — when a user makes a query the server traverses a graph of your data, with types all pointing to each other. We aim to make a comprehensive data graph that feels intuitive to the end user and is trivial to maintain and expand.



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GDA is developing the decentralized financial application development environment and rapid financial engineering protocol built on Ethereum.