The author recounts their four-month journey building a simplified, in-memory, relational database in Rust. Motivated by a desire to deepen their understanding of database internals, they leveraged 647 open-source crates, highlighting Rust's rich ecosystem. The project, named "Oso," implements core database features like SQL parsing, query planning, and execution, though it omits persistence and advanced functionalities. While acknowledging the extensive use of external libraries, the author emphasizes the value of the learning experience and the practical insights gained into database architecture and Rust development. The project served as a personal exploration, focusing on educational value over production readiness.
The blog post "Build a Database in Four Months with Rust and 647 Open-Source Dependencies" by Tison Kun details the author's journey of creating a simplified, in-memory, relational database prototype named "TwinDB" using the Rust programming language. The project, undertaken over a four-month period, heavily leveraged the rich ecosystem of open-source Rust crates, accumulating a dependency tree of 647 distinct packages. This reliance on existing libraries is presented as both a strength and a potential complexity, highlighting the trade-offs involved in rapid prototyping versus ground-up development.
Kun outlines the core features implemented in TwinDB, including SQL parsing utilizing the sqlparser-rs crate, query planning and optimization strategies, and a rudimentary execution engine. The database supports fundamental SQL operations like SELECT, INSERT, and CREATE TABLE, enabling basic data manipulation and retrieval. The post emphasizes the learning process involved in understanding database internals, such as query processing, transaction management (although only simple transactions are implemented), and storage engine design. Notably, TwinDB employs an in-memory store for simplicity, meaning data is not persisted to disk.
The author delves into specific technical challenges encountered during development, particularly regarding the integration and management of numerous external dependencies. The experience of wrestling with varying API designs and occasional compatibility issues is discussed. Despite the inherent complexities introduced by a large dependency graph, Kun advocates for the accelerated development speed enabled by leveraging the open-source ecosystem. The blog post underscores the pragmatic approach of prioritizing functionality over reinventing the wheel, especially in a prototype setting.
The post concludes with reflections on the lessons learned, including a deeper appreciation for the intricacies of database systems and the power of Rust's robust type system and performance characteristics. It also alludes to potential future improvements for TwinDB, albeit without concrete commitments. The overall tone conveys enthusiasm for Rust and its ecosystem, portraying it as a viable choice for undertaking ambitious projects like database development. The project is explicitly framed as a learning exercise and a demonstration of Rust's capabilities, rather than a production-ready database solution. The 647 dependencies are presented not as a negative aspect, but as a testament to the richness and reusability of the Rust open-source landscape.
Summary of Comments ( 24 )
https://news.ycombinator.com/item?id=42711727
Hacker News commenters discuss the irony of the blog post title, pointing out the potential hypocrisy of criticizing open-source reliance while simultaneously utilizing it extensively. Some argued that using numerous dependencies is not inherently bad, highlighting the benefits of leveraging existing, well-maintained code. Others questioned the author's apparent surprise at the dependency count, suggesting a naive understanding of modern software development practices. The feasibility of building a complex project like a database in four months was also debated, with some expressing skepticism and others suggesting it depends on the scope and pre-existing knowledge. Several comments delve into the nuances of Rust's compile times and dependency management. A few commenters also brought up the licensing implications of using numerous open-source libraries.
The Hacker News post titled "Build a Database in Four Months with Rust and 647 Open-Source Dependencies" (linking to tisonkun.io/posts/oss-twin) generated a fair amount of discussion, mostly centered around the number of dependencies for a seemingly simple project.
Several commenters expressed surprise and concern over the high dependency count of 647. One user questioned whether this was a symptom of over-engineering, or if Rust's crate ecosystem encourages this kind of dependency tree. They wondered if this number of dependencies would be typical for a similar project in a language like Go. Another commenter pondered the implications for security audits and maintenance with such a large dependency web, suggesting it could be a significant burden.
The discussion also touched upon the trade-off between development speed and dependencies. Some acknowledged that leveraging existing libraries, even if numerous, can significantly accelerate development time. One comment pointed out the article author's own admission of finishing the project faster than anticipated, likely due to the extensive use of crates. However, they also cautioned about the potential downsides of relying heavily on third-party code, specifically the risks associated with unknown vulnerabilities or breaking changes in dependencies.
A few commenters delved into technical aspects. One user discussed the nature of transitive dependencies, where a single direct dependency can pull in many others, leading to a large overall count. They also pointed out that some Rust crates are quite small and focused, potentially inflating the dependency count compared to languages with larger, more monolithic standard libraries.
Another technical point raised was the difference between a direct dependency and a transitive dependency, highlighting how build tools like Cargo handle this distinction. This led to a brief comparison with other languages' package management systems.
The implications of dependency management in different programming language ecosystems was another recurrent theme. Some commenters with experience in Go and Java chimed in, offering comparisons of typical dependency counts in those languages for similar projects.
Finally, a few users questioned the overall design and architecture choices made in the project, speculating whether the reliance on so many crates was genuinely necessary or if a simpler approach was possible. This discussion hinted at the broader question of balancing code reuse with self-sufficiency in software projects. However, this remained more speculative as the commenters did not have full access to the project's codebase beyond what was described in the article.