A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases (like SQL, Oracle, etc.). Types of NoSQL databases:
MongoDB does not use conventional locking with reduction, as it is planned to be light, high-speed and knowable in its presentation. It can be considered as parallel to the MySQL MyISAM auto entrust sculpt. With simplest business sustain, performance is enhanced, particularly in a structure with numerous servers.
MongoDB stores BSON (Binary Interchange and Structure Object Notation) objects in the collection. The concatenation of the collection name and database name is called a namespace.
MongoDB allows a highly flexible and scalable document structure. For e.g. one data document in MongoDB can have five columns and the other one in the same collection can have ten columns. Also, MongoDB database are faster as compared to SQL databases due to efficient indexing and storage techniques.
No. MongoDB does not support such relationships. By default MongoDB does not support such primary key - foreign key relationships. However, we can achieve this concept by embedding one document inside another. Foe e.g. an address document can be embedded inside customer document.
No. MongoDB does not support default multi-document ACID transactions. However, MongoDB provides atomic operation on a single document.
ObjectID is a 12-byte BSON type with:
Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement. If an appropriate index exists for a query, MongoDB can use the index to limit the number of documents it must inspect.
Aggregations operations process data records and return computed results. Aggregation operations group values from multiple documents together, and can perform a variety of operations on the grouped data to return a single result. MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function, and single purpose aggregation methods and commands.
Sharding is a method for storing data across multiple machines. MongoDB uses sharding to support deployments with very large data sets and high throughput operations.
Replication is the process of synchronizing data across multiple servers. Replication provides redundancy and increases data availability. With multiple copies of data on different database servers, replication protects a database from the loss of a single server. Replication also allows you to recover from hardware failure and service interruptions.
Primary and master nodes are the nodes that can accept writes. MongoDB's replication is 'single-master:' only one node can accept write operations at a time. Secondary and slave nodes are read-only nodes that replicate from the primary.
When running a 32-bit build of MongoDB, the total storage size for the server, including data and indexes, is 2 gigabytes. For this reason, do not deploy MongoDB to production on 32-bit machines. If you're running a 64-bit build of MongoDB, there's virtually no limit to storage size.
A storage engine is the part of a database that is responsible for managing how data is stored on disk. For example, one storage engine might offer better performance for read-heavy workloads, and another might support a higher-throughput for write operations.
The database profiler collects fine grained data about MongoDB write operations, cursors, database commands on a running mongod instance. You can enable profiling on a per-database or per-instance basis. The database profiler writes all the data it collects to the system.profile collection, which is a capped collection.
Mongo-DB is a document database which provides high performance, high availability and easy scalability.