Are there hidden issues when using a Git repository for storing structured documents instead of a traditional document database? Consider performance, reliability, and scalability in such an unconventional design.
yeah, git is meant for version control not a database. best to use a dedicated db backend for scale or speed. issues may include race conitions and poor query performance. small projects might work, but becomes problematic when intened as a full backend.
hey, im wonderin if adding some db-look features to a git repo might ease those merge conflicts? how do y’all handle intense write burst setups? any clever hacks yuo noticed in a hybrid approach?
i think using git as a db is a neat hack for very basic use but it hits snags quicklly on scale and contention. it’s fun for versioning, not a replacement for a real, robust database in production environments.
A Git repository is primarily designed to track and manage source code changes rather than serve as a reliable and scalable database backend. While determining the system state through commits is interesting from a version-controlled perspective, it does not support optimized querying or efficient concurrent modifications. In practical experiences, limitations become evident in performance when handling larger payloads or multiple simultaneous accesses. Though it may work for simple use cases with low transaction rates, extensive usage often reveals inherent constraints with reliability and scalability compared to dedicated document databases.
The concept of using a Git repository as your database is creative but comes with significant trade-offs. My experience shows that while versioning offers unique benefits, operational concerns quickly overshadow them. Git is not designed for indexing or real-time queries, so performance degrades as records increase. Concurrent modifications often lead to complex merge conflicts that require custom conflict resolution logic. I found a shift to purpose-built solutions more reliable, particularly when working with flexible query requirements and higher throughput scenarios.