An open-source accounting system with gRPC endpoints and SQL backends for programmable double-entry bookkeeping.
GoDBLedger is an open-source accounting system that provides programmable double-entry bookkeeping via gRPC endpoints and SQL backends. It allows users to automate financial transactions and store data in their own databases, enabling full control over financial processes. The system includes tools for transaction submission, reporting, and generating PDF financial statements.
Businesses and individuals who want to self-host their accounting system, automate financial data entry, and analyze financial data using custom software. It's ideal for those who prefer programmatic control over their financial processes.
Developers choose GoDBLedger for its gRPC API, which enables seamless integration with scripts and applications, and its clear SQL schema that allows direct database querying. Its self-hosted nature ensures data privacy and control, distinguishing it from cloud-based alternatives.
Accounting Software with GRPC endpoints and SQL Backends
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Provides a gRPC endpoint for submitting transactions programmatically, enabling seamless automation from custom applications, as shown in the included Python client example.
Stores data in SQLite3 or MySQL with a transparent schema, allowing direct querying and analysis with preferred tools, as evidenced by the sample SQL queries in the README.
Supports deployment on Linux servers, Raspberry Pi, or via Docker and Kubernetes, ensuring full data control without cloud dependency, with detailed docker-compose and Kubernetes examples provided.
Processes ledger files for integration with existing accounting tools, leveraging forked ledger-cli functionality to maintain compatibility with legacy systems.
Requires server setup, database configuration, and gRPC knowledge, with additional dependencies like Node.js for PDF generation, increasing deployment overhead compared to turnkey solutions.
The reporter tool offers only basic Profit and Loss and Balance Sheet reports; advanced financial analysis demands custom SQL queries or handlebars templates, which may not suffice for complex business needs.
Relies on a wiki and demo video for guidance, with few client libraries available (only Python example given), potentially slowing integration and troubleshooting for less common use cases.