MongoDB vs SQLite
A side-by-side technical matrix of MongoDB (Databases & Cache) and SQLite (Databases & Cache) — summaries, strengths and structural trade-offs, symmetrically laid out.
MongoDB
MongoDB is a document database storing flexible JSON-like records, designed for horizontal scaling through built-in sharding and replica sets. Its query API maps naturally to objects in application code.
Pros
- Flexible schema. Documents evolve without migrations, speeding early product iteration. 0
- Built-in sharding. Horizontal write scaling is a first-class, supported feature. 0
- Developer ergonomics. JSON documents map directly to application objects. 0
- Atlas managed service. The official cloud handles backups, scaling, and search. 0
Cons
- Join limitations. Relational queries need $lookup stages that strain performance. 0
- Schema drift risk. Flexibility without discipline produces inconsistent documents. 0
- Memory hungry. The working set must fit in RAM for good performance. 0
- SSPL license. The non-OSI license restricts offering MongoDB as a service. 0
- Transaction overhead. Multi-document transactions cost noticeably more than single-document writes. 0
SQLite
SQLite is a serverless, embedded relational database that stores an entire database in a single file. It is the most deployed database engine in the world, shipping inside phones and browsers.
Pros
- Zero configuration. No server to run; the whole database is one portable file. 0
- Incredibly reliable. Exhaustive testing makes it famously crash-resistant. 0
- Fast for local reads. In-process access beats any network database for latency. 0
- Everywhere. Ships in every phone, browser, and countless apps. 0
Cons
- Limited concurrency. A single writer lock bottlenecks write-heavy workloads. 0
- Not for big scale. Poor fit for high-traffic multi-server applications. 0
- Loose typing. Flexible column types can mask data errors. 0
- No network access. Being embedded means no built-in client-server mode. 0