MongoDB is a cross-platform document-oriented database program.
Classified as a NoSQL database program, it stores data in flexible, JSON-like documents, meaning fields can vary from document to document, and data structure can be changed over time. The document model maps to the objects in your application code, making data easy to work with.
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Frequently Asked Questions
The system requirements for deploying MongoDB can vary depending on your specific use case, such as the expected workload, data volume, and the desired level of performance and availability. General guidelines for system requirements include:
MongoDB is supported on various operating systems, including Linux (e.g., Ubuntu, CentOS, Red Hat), Windows, and macOS.
MongoDB can run on multi-core processors. The specific CPU requirements will depend on the expected workload and concurrent operations. Generally, a multi-core CPU is recommended for better performance.
The amount of RAM required depends on the size of your dataset and the working set. As a general guideline, MongoDB recommends having enough RAM to fit the active working set in memory to achieve optimal performance, which they estimate as 4 GB at the least.
MongoDB uses disk storage for data persistence. The specific storage requirements depend on the size of your dataset and the rate of data growth, but you’ll need to have at least 10 GB not including the space for storing your data.
MongoDB operates over TCP/IP, so ensure a reliable and low-latency network connection. Network bandwidth requirements will vary based on the volume of incoming and outgoing data.
Virtualization and Containerization:
MongoDB can be deployed within virtualized environments like VMware or containerized using Docker and Kubernetes. Ensure that the virtualization or containerization platform you choose is well-suited for database workloads.
MongoDB is often used for content management systems, real-time analytics, e-commerce platforms, mobile applications, IoT (Internet of Things) data storage, and any application that benefits from flexible and scalable data storage.
When looking for a NoSQL database, there are several popular alternatives to MongoDB, including Couchbase, Cassandra, Redis, Amazon DynamoDB, HBase, Neo4j, and ArangoDB.
MongoDB is non-relational, meaning it does not require a fixed schema. It stores data in BSON (Binary JSON) format and uses a flexible, document-based data model, making it well-suited for semi-structured and unstructured data.
MongoDB uses a rich query language that includes support for filtering, projection, and aggregation. Queries can be performed using the MongoDB Query Language (MQL) or using the MongoDB Compass graphical interface.