Why Everyone Is Talking About SQLite?

**1. The Limits of SQLite: Where Does It Break?** Suggest using SQLite in production, and the first response you’ll hear is, *“Won’t that break?”* For years, the answer was a firm **yes**—at least for high-traffic, multi-user applications. And even today, SQLite has real **technical constraints** that developers need to understand before adopting it. **Where SQLite Struggles in Production** ### 🔴 **Write Contention** - SQLite uses a **single-writer model**, meaning only one transaction can write to the database at a time, while multiple transactions can read concurrently. In **WAL mode**(Write-Ahead Logging), concurrent reads and writes are possible, but only one write transaction can be committed at a time, which can still lead to contention under heavy write loads. **Workarounds:** - Enabling **WAL mode**(Write-Ahead Logging) helps by allowing multiple readers to access the database while a write transaction is ongoing. However, there’s still a ceiling because only one write operation can be performed at a time. When concurrent writes pile up, transactions start queuing, leading to slowdowns. This limitation makes SQLite less ideal for high-write workloads where multiple users frequently update data. - Some applications **batch writes**or offload them to a queue. - Enabling ### 🔴 **Scaling and Network Limitations** - SQLite was designed to be used **locally**, not over a networked filesystem like NFS or SMB. Doing so can cause **locking issues, performance degradation, and even data corruption.**Additionally, **SQLite does not scale horizontally**the way traditional databases do, as it lacks built-in support for distributed nodes and multi-writer replication. … These solutions help mitigate SQLite’s traditional limitations by adding replication and distributed capabilities, but they do not eliminate the single-writer model. While they enhance availability and redundancy, SQLite still operates with a single-writer architecture, meaning write contention can still be a concern in high-throughput environments. If high availability and true multi-writer clustering are key, a traditional database like Postgres or MySQL is