MongoDB is for
Who uses MongoDB?
How does MongoDB work?
MongoDB stores data using a flexible document data model that is similar to JSON. Documents contain one or more fields, including arrays, binary data and sub-documents. Fields can vary from document to document. This flexibility allows development teams to evolve the data model rapidly as their application requirements change. When you need to lock down your data model, optional document validation enforces the rules you choose.
Developers access documents through rich, idiomatic drivers available in all popular programming languages. Documents map naturally to the objects in modern languages, which allows developers to be extremely productive. Typically, there’s no need for an ORM layer.
MongoDB provides auto-sharding for horizontal scale out. Native replication and automatic leader election supports high availability across racks and data centers. And MongoDB makes extensive use of RAM, providing in-memory speed and on-disk capacity.
Unlike most NoSQL databases, MongoDB provides comprehensive secondary indexes, including geospatial and text search, as well as extensive security and aggregation capabilities. MongoDB provides the features you need to develop the majority of the new applications your organization develops today.
Going beyond the core document model, MongoDB offers multimodel capabilities. In-database analytics, graph, cross-document relations, search, faceted navigation, and more make MongoDB suitable for all use cases. For further workload customization, MongoDB offers a pluggable storage engine API, with multiple storage engines available. Select your storage engine based on your application requirements, and even mix storage engines within a replica set. The WiredTiger storage engine delivers great overall performance, the encrypted storage engine provides encryption of data at rest, and the in-memory storage engine offers the predictable low latency of in-memory computing.
Our customers are running MongoDB on
We’re delivering millions of IOPS, and handling more than
documents in production