1. Document-Oriented:
- MongoDB is a document-oriented database, which means it stores data in flexible, JSON-like documents. Each document can have its own structure and can contain nested data structures, arrays, and other complex data types.
2. No Schema Constraints:
- Unlike relational databases, MongoDB does not enforce a fixed schema for documents. This allows for dynamic and evolving data models, where documents within the same collection can have different fields and structures.
3. Scalability:
- MongoDB is designed for horizontal scalability, allowing it to handle large volumes of data and high throughput workloads. It supports sharding, which involves distributing data across multiple servers or clusters, and replication for high availability and fault tolerance.
4. Querying and Indexing:
- MongoDB provides powerful querying capabilities using a rich query language and supports secondary indexes to optimize query performance. It also supports aggregation pipelines for complex data transformations and analysis.
5. High Performance:
- MongoDB is optimized for performance, with features such as in-memory storage, asynchronous I/O operations, and efficient query execution plans. It can handle real-time analytics, high concurrency, and low-latency applications.
6. Ad Hoc Queries:
- MongoDB supports ad hoc queries, allowing developers to query data using a flexible query language similar to SQL. This makes it easy to explore and analyze data without predefined schemas or complex join operations.
7. Replication and Fault Tolerance:
- MongoDB uses replica sets for automatic failover and data redundancy. Each replica set consists of multiple nodes, including primary and secondary nodes, which replicate data asynchronously to ensure data durability and availability.
8. Horizontal Partitioning:
- MongoDB supports sharding, which involves splitting data across multiple shards or partitions based on a shard key. This allows MongoDB to distribute data and workload evenly across multiple servers, improving scalability and performance.
9. Geospatial Indexing:
- MongoDB supports geospatial indexing and querying, allowing developers to store and query location-based data such as coordinates, polygons, and bounding boxes. This is useful for applications involving mapping, geolocation, and spatial analysis.
10. Community and Ecosystem:
- MongoDB has a large and active community of developers, administrators, and contributors who provide support, documentation, and third-party tools and libraries. It also offers commercial support, training, and consulting services for enterprise users.