We’ll give a thorough comparison of MongoDB versus SQLite in this article.
Overview of MongoDB and SQLite
MongoDB is an open-source, NoSQL document-based database that offers flexibility and scalability for modern applications. Large amounts of data, especially unstructured data, may be stored and managed with this system.
In contrast, SQLite is a compact, file-based relational database management system (RDBMS). Small-scale applications and embedded systems both frequently use it. SQLite stores data in a single file, making it easy to deploy and manage. It supports standard SQL queries and transactions while requiring minimal configuration.
The following aspects show the performance comparison of MongoDB and SQLite.
1: Comparison of Query Performance
When comparing MongoDB and SQLite, a crucial factor to consider is their performance when searching for information in databases. MongoDB offers versatility by allowing data exploration through all document fields, which is a valuable asset. Additionally, MongoDB boasts indexing as a feature for quick and efficient data retrieval. Its impressive capabilities provide fast search results, particularly when processing vast amounts of data.
In contrast, SQLite uses SQL as its language for searching data in the database. The use of SQL queries and indexes offers exceptional efficiency when searching for data, making it a valuable tool. However, its performance may deteriorate when used with large databases, leading to reduced efficiency and slower processing speeds. Therefore, if you have smaller or medium-sized amounts of data, SQLite can deliver fast results and perform efficiently.
2: Speed Comparison Between MongoDB and SQLite
We may evaluate the performance of these databases using benchmarks to see if MongoDB is quicker than SQLite. One benchmark is the Decision Support Benchmark (TPC-H), which measures the database’s performance in handling complex queries and data manipulation tasks. In a study, MongoDB performed better than SQLite in the TPC-H test, with a query time of 0.82 seconds compared to SQLite’s 2.66 seconds.
Another benchmark is the Cloud Serving Benchmark (YCSB), which tests the performance of databases under different workloads, such as read-heavy and write-heavy workloads. In a YCSB benchmark, a study shows that MongoDB had a higher throughput than SQLite under read-heavy workloads. However, under write-heavy workloads, SQLite had a higher throughput than MongoDB. This suggests that the database choice depends on the specific use case and workload.
3: Memory Usage and Disk Space
Memory use and disk space should also be taken into account when contrasting MongoDB vs SQLite’s performance. SQLite uses less memory than MongoDB, making it an ideal choice for applications with limited memory resources. However, MongoDB uses less disk space than SQLite as it stores data in JSON-like documents, making it more suitable for applications involving large amounts of unstructured data.
4: Scalability
when selecting one for modern applications. MongoDB stands out with its built-in capacity for horizontal scalability, which enables effortless expansion to accommodate additional users and data. Additionally, MongoDB’s sharding functionality enables data distribution across several servers, leading to improved performance and high availability. In contrast, SQLite is designed to work with local databases and is not optimized for scaling out. It is primarily intended for usage on a single device or application.
5: Security
Security is a critical factor when choosing a database. MongoDB provides features such as role-based access control, encrypted storage, and secure network communication to ensure data privacy and integrity. On the other hand, SQLite does not have native security features and must rely on the application layer to implement security measures.
6: Use Case Considerations
It is crucial to take the application’s needs and individual use cases into account when comparing the performance of MongoDB versus SQLite. MongoDB excels in handling massive amounts of unstructured data, complex queries, and high concurrency. It is a great option for software that needs adaptable data models, real-time analytics, and quick development times. On the other hand, SQLite excels in situations when simplicity, usability, and a small resource footprint are crucial. It is the best option for applications that run on a single workstation, have modest data storage needs, and require immediate access to local data.
Conclusion
MongoDB is faster than SQLite in some areas, such as handling complex queries and read-heavy workloads. However, SQLite excels in areas such as write-heavy workloads and memory usage. The choice of a database depends on specific requirements, such as scalability, security, disk space, and memory usage.
