ProtoQL: A Work-in-Progress ORM Bridging Protocol Buffers and Key-Value Stores

ProtoQL is an emerging open-source project aiming to provide a novel way to manage structured data using protocol buffers within a key-value store environment. It seeks to combine the strengths of both worlds, offering the schema definition and data serialization advantages of protocol buffers with the scalability and performance benefits of key-value stores.

Key Features

• Schema Evolution: ProtoQL leverages the protocol buffer’s established approach to schema evolution, allowing applications to adapt incrementally without requiring centralized schema management.
• Efficient Updates: By encoding paths within keys, updates can be performed on individual fields without rewriting entire objects, leading to significant performance gains over traditional approaches.
• Embedded Maps: ProtoQL supports nested maps within protocol buffer schemas, enabling flexible data representation and the ability to add or remove map elements without restructuring the entire object.

How it Works

ProtoQL utilizes a unique algorithm for reconstructing protocol buffers from individual key-value pairs retrieved through range scans on the underlying key-value store. The project is currently written in Rust, known for its performance, memory safety, and concurrency features.

• Query Language: Inspired by GraphQL, ProtoQL’s query language aims to provide a user-friendly and expressive way to access and manipulate data within the protocol buffer schema. While core functionalities like filtering, sorting, aggregation, and joins are envisioned, they are not yet implemented.

Current Status & Future Plans

ProtoQL is actively being developed and remains a work in progress. Key milestones include:

• Completing the implementation of query language features such as filtering, sorting, aggregation, and joins.
• Conducting thorough performance benchmarks to demonstrate ProtoQL’s efficiency and scalability compared to existing ORM solutions.

• Building a vibrant community around ProtoQL through documentation, tutorials, and open-source contributions.

• Production Readiness: The ultimate goal is to make ProtoQL production-ready, offering a robust and reliable solution for managing structured data within key-value store environments.

Conclusion

ProtoQL holds significant promise as a novel approach to ORM in the realm of protocol buffers and key-value stores. Its unique features and ambitious roadmap position it as a potential game-changer in the world of data management. With continued development and community support, ProtoQL could become a powerful tool for developers seeking efficient and scalable solutions for structured data handling.

As an experiment, this project brought to you using large language models

Here’s a link to the project’s GitHub repository.