SQLite Vs MongoDB

SQLite and MongoDB are both popular databases, but they differ significantly in their structure, use cases, and capabilities. Here's a comparison between the two:

1. Database Type

SQLite:

• Relational (SQL) Database.Uses a structured schema and supports SQL queries.Data is stored in tables with rows and columns, and you use SQL (Structured Query Language) for interacting with it.

MongoDB:

• NoSQL (Document-oriented) Database.Uses a flexible, schema-less structure that stores data in JSON-like documents (BSON - Binary JSON).
• Ideal for unstructured data or when you need high flexibility with the schema.

2. Data Storage Model

SQLite:

• Relational: Stores data in tables with predefined columns, rows, and relationships between tables using foreign keys.
• The data is structured and normalized, with strict schemas.

MongoDB:

• Document-based: Stores data in BSON (Binary JSON) format, allowing for complex nested structures (arrays, objects).
• Schema-less: Documents within a collection can have different fields and structures.

3. Use Cases

SQLite:

• Best for applications that need a lightweight, embedded database with local storage.
• Commonly used for desktop applications, mobile apps, or small-to-medium-sized web applications.
• Perfect for situations where you need a serverless, self-contained database.

MongoDB:

• Best suited for applications with large, unstructured data or rapidly changing schemas.
• Common use cases include big data, content management systems, real-time analytics, IoT applications, and applications requiring fast development and flexible data models.
• Widely used in large-sc

4. Schema

SQLite:

• Structured schema: Tables and columns must be defined upfront.Data is organized in a relational format, requiring normalization.

MongoDB:

• Flexible, schema-less: Documents in a collection don’t need to have the same structure. You can change the schema easily as your application evolves.Ideal for cases where the data structure is not fixed or is frequently evolving.

5. Query Language

SQLite:

• Uses SQL (Structured Query Language), which is a powerful, standardized language for managing relational databases.
• Supports complex joins, aggregations, and transactions.

MongoDB:

• Uses its own query language, which is JavaScript-like. It doesn't use SQL and supports querying JSON-like documents.
• Provides advanced features like aggregation pipelines for more complex queries.

6. Scalability

SQLite:

• Not designed for horizontal scaling or large-scale applications.
• Works well for small to medium applications but struggles with concurrent write-heavy workloads or large-scale data.

MongoDB:

• Designed for horizontal scalability with support for sharding (splitting data across multiple servers).
• Ideal for handling very large datasets and high-volume workloads.

7. Transactions and ACID Compliance

SQLite:

• Fully ACID-compliant (Atomic, Consistent, Isolated, Durable).
• Supports transactions, ensuring reliability and consistency, but it’s more limited in concurrent access (mainly single-threaded).

MongoDB:

• Supports ACID transactions (since version 4.0) across a single replica set or within a sharded cluster.
• Provides more flexibility with eventual consistency models in some use cases but also allows for strong consistency when needed.

8. Performance

SQLite:

• Very fast for read-heavy operations or small databases, as it's embedded and runs locally.
• Performance can degrade under heavy writes, particularly when there are many concurrent users.

MongoDB:

• Optimized for high-performance read and write operations, especially with large-scale applications.
• The performance can vary based on data modeling and indexing but scales well for large workloads.

9. Deployment

SQLite:

• Serverless: No need for a dedicated server; the database is embedded within the application. The database is stored in a single file.
• Easy to deploy as it doesn’t require a complex infrastructure.

MongoDB:

• Requires a server or cloud infrastructure (self-hosted or managed cloud solution like MongoDB Atlas).Can be deployed on a single machine or across distributed clusters for scaling.

10. Licensing

SQLite:

• Open-source and free to use under the public domain.

MongoDB:

• Open-source (under the Server Side Public License, SSPL) but with more restrictions compared to SQLite.
• Commercial licenses available for enterprise users through MongoDB, Inc.

11. Backup and Recovery

SQLite:

• Backup is typically done by copying the database file while the application is not writing to it.
• Simpler backup procedures but no built-in tools for replication or high availability.

MongoDB:

• Offers advanced backup and recovery features, including replication, sharding, and tools for hot backups.
• Supports point-in-time backups with replication for high availability.

Summary

When to Use Which:

• SQLite:Choose SQLite if you need a lightweight, simple, self-contained database for a small project, local app, or mobile app where you don’t need to scale horizontally or have complex relationships between data.
• MongoDB:Choose MongoDB if you need a highly scalable, flexible, and distributed database, especially if your data structure is evolving or not strictly relational, and you are building large-scale web apps, real-time analytics, or applications requiring high availability and performance.

Both databases have their strengths, and the choice largely depends on the specific requirements of your application.

Nadir Riyani holds a Master in Computer Application and brings 15 years of experience in the IT industry to his role as an Engineering Manager. With deep expertise in Microsoft technologies, Splunk, DevOps Automation, Database systems, and Cloud technologies? Nadir is a seasoned professional known for his technical acumen and leadership skills. He has published over 225 articles in public forums, sharing his knowledge and insights with the broader tech community. Nadir's extensive experience and contributions make him a respected figure in the IT world.