LevelDB vs MongoDB: What are the differences?
Introduction
This markdown provides a comparison between LevelDB and MongoDB, highlighting the key differences between the two databases.
1. Data Model:
LevelDB is a key-value store that supports only one key-value pair for every given key. On the other hand, MongoDB is a document-oriented database that allows the storage of structured and semi-structured documents (JSON-like), providing more flexibility in data modeling.
2. Atomicity:
LevelDB supports atomic operations at the write operation level, meaning either a write operation is performed completely or not at all. In contrast, MongoDB supports atomicity at the document level, where an operation can involve multiple fields or modifications within a single document.
3. Query Language:
LevelDB does not provide a direct query language or support complex queries. It focuses on simple read and write operations. MongoDB, however, offers a powerful query language called MongoDB Query Language (MQL), which allows complex and versatile querying capabilities.
4. Scalability:
LevelDB is a single-node database, making it challenging to scale and distribute across multiple nodes for high availability. MongoDB, on the other hand, is designed for scalability and supports horizontal scaling by distributing data across multiple nodes, providing better performance and fault tolerance.
5. Indexing:
LevelDB uses a simple key-based indexing, and it does not support secondary indexes. MongoDB, in contrast, provides rich indexing capabilities, including primary and secondary indexes, supporting faster search operations and efficient data retrieval.
6. Data Consistency:
LevelDB guarantees strong consistency, where after a write operation, the read operation will always return the latest state. MongoDB, by default, provides eventual consistency, where after a write operation, there might be a slight delay for the changes to propagate and become visible for read operations.
In summary, LevelDB is a lightweight key-value store with limited data modeling and querying capabilities, while MongoDB is a feature-rich document-oriented database that supports complex queries, scalability, indexing, and eventual consistency.
