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Graph database written in C and Haskell with an emphasis on extreme performance

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infinitydb

Graph database written in C with an emphasis on extreme performance

infinitydb is a graph database that is able to index a tremendous amount of data, and rapidly retrieve what the end user needs.

There isn't really a good graph database in the market right now. There is Neo4J which doesn't work very well and costs money, and there is China's NebulaGraph, which is used because China has a huge need for organizing HUGE amounts of data that no relational database could handle.

Many in industry won't admit it because they have invested so much in relational databases, but relational databases suck. It seems to me that almost anything in the world can be modeled with a graph database, so why not build the world's best one?

DEVELOPERS - your future:

By helping work on this project, you will be helping to build one of the world's fastest databases available. I believe this database is going to be so good that the worlds largest companies are going to use it. You will be helping power the most widespread database in the world that nearly everything is going to run on. It's going to be HUGE and you might be contributing to one of the world's most impactful projects.

Chosen language - I chose to write this database in C because that is one of the most performant languages available. Performance is a huge objective of this database.

Simplicity - One goal in this project is to keep this database extremely minimal and lean. The focus should be on RAPID retrieval of data so that end users can use the data immediately. Extraneous features were kept to a bare minimum because we didn't want to bog down the system with extra code that won't be used or takes too long to execute.

Continuous improvement - another goal is to continually optimize algorithms to take the least amount of time possible. This is going to help us build a state of the art database that destroys any competition.

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Graph database written in C and Haskell with an emphasis on extreme performance

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