In building any technology there are always trade-offs when squeezing maximum performance out of the implementation so knowing what that guiding light is for a technology becomes very important. If you’re trying to do everything, or even too many things, odds are none if it will be great because you can’t go all out for one primary objective. Your focus will be split.
This becomes especially important when evaluating the graph database landscape where you have implementations that range from
- doing only edge caching or single hop queries by using focused indexing strategies
- to graph layers on top of existing database that still will suffer during complex graph traversals due to the underlying data storage implementation, which also restricts them from being able to guarantee the consistency of a relationship between two nodes on write
- to various hybrids such as combining document with graph that try to do it all, but ultimately end up doing neither well
- to fully native graph implementations that are designed for optimal graph traversal and navigation throughout the set of connected data
It’s key to understand these aspects of the underlying database implementation and the guiding light. Be wary of graph hybrids because they have a split focus on where they optimize. The saying, “Jack of trades; master of none” isn’t just true for people. If you’ve been creating technology for any period of time you
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