Went through GRVT's ticker feed structure today, mostly becuase understanding what a single ticker update actually carries matters for closing out the market data picture Ive been building across this sprint.
A ticker presumably surfaces last traded price, 24 hour high and low, 24 hour volume, and likely percentage change over that same window, updated as a compact snapshot rather then requiring a client to derive these statistics themselves from raw trade history.
What I find notable is that this is fundamentally a convenience layer sitting on top of data thats technically derivable from the trades feed I looked at previously. A client could theoretically compute 24 hour high, low, and volume by processing the full trade history themselves, but GRVT computing and streaming that summary directly removes real computational burden from every single client that would otherwise need to maintain the same rolling calculation independently.
This connects to a pattern Ive noticed across GRVT's broader feed design this week, raw granular data exists, orderbook depth, individual trades, but summarized, pre-computed views exist alongside them for cases where the full detail isnt actually necessary.
Closing this sprint on the observation that GRVT's API surface seems consistently designed around this same tradeoff, granular data for those who need precision, summarized data for those who just need an accurate picture quickly.
@grvt_io #grvt
A ticker presumably surfaces last traded price, 24 hour high and low, 24 hour volume, and likely percentage change over that same window, updated as a compact snapshot rather then requiring a client to derive these statistics themselves from raw trade history.
What I find notable is that this is fundamentally a convenience layer sitting on top of data thats technically derivable from the trades feed I looked at previously. A client could theoretically compute 24 hour high, low, and volume by processing the full trade history themselves, but GRVT computing and streaming that summary directly removes real computational burden from every single client that would otherwise need to maintain the same rolling calculation independently.
This connects to a pattern Ive noticed across GRVT's broader feed design this week, raw granular data exists, orderbook depth, individual trades, but summarized, pre-computed views exist alongside them for cases where the full detail isnt actually necessary.
Closing this sprint on the observation that GRVT's API surface seems consistently designed around this same tradeoff, granular data for those who need precision, summarized data for those who just need an accurate picture quickly.
@grvt_io #grvt