Index

The GitQL Query engine is designed to work as a set of decoupled libraries which gives you the flexibility to extend or replace any part of the query execution journey.

GitQL Engine Architecture

graph LR
  A[SQL Query] --> B[Tokenizer];
  B --> C[Parser and Type Checker];
  C --> D[Execution Engine];
  D --> E[Output]
  F[Schema] --> C;
  G[Data Provider] --> D;
  H[Standard library] --> D;

GitQL SDK Components

Component	Description	Install
gitql-core	Core components	cargo install gitql-core
gitql-std	Standard library functions	cargo install gitql-std
gitql-cli	CLI components like args parser, cli reporter	cargo install gitql-cli
gitql-ast	structures components such as AST, Types	cargo install gitql-ast
gitql-parser	Parser and Type checker components	cargo install gitql-parser
gitql-engine	Execution engine component	cargo install gitql-engine

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Using the GitQL SDk to extend the components

As you will see building your own query language for specific need using the GitQL gives you the ability to customize every part of the engine such as operators, types, schema, functions ...etc.

• Customize the Data Schema.
• Customize the Data Provider.
• Customize the Standard library.
• Customize the Type system.
• Customize the Value system.

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Example of product that build on top of GitQL

• ClangQL: To run SQL query on C/C++ Code.

• FileQL: To run SQL query on the file system.

• LLQL: Tool to run SQL query on LLVM IR/BC and perform Pattern matching on instructions.

• PyQL: To run SQL query on Python Code.

Feel free to add your product too, everyone is welcome to join.