What is MongoDB?
What is NoSQL Database?
NoSQL is termed as "Not Only SQL" or "Non-Relational" which is a mechanism to store and process data without following the traditional database approach such as storing data in the table format. NoSQL database has no schema and the structure used by NoSQL databases are key-value pair, document, wide column, graph.
The following is the types and classification of NoSQL databases.
1. Wide Column NoSQL Databases
The Wide column is the type of NoSQL database that uses the column rows and tables but the table’s column name formats can be changes from row to row. Examples of wide columns NoSQL databases are Cassandra, Azure Cosmos DB, HBase, Accumulo, Scylla.
2. Document Type NoSQL Databases
The Document is also a type of NoSQL database that is used to store and process semi-structured data. An example of the Document NoSQL database is ArangoDB, RethinkDB, Azure Cosmos DB, Couchbase, MongoDB, Apache CouchDB, Clusterpoint, IBM Domino, BaseX, OrientDB, eXist-db, Qizx, MarkLogic.
3. Graph Type NoSQL Databases
The Graph is also a type of NoSQL database which stores the detail of network data. The example of Graph NoSQL databases is AgensGraph, InfiniteGraph, Azure Cosmos DB, MarkLogic, ArangoDB, AllegroGraph, OrientDB, Virtuoso, Apache Giraph, Neo4J.
4. Key–Value Type NoSQL Databases
The Key-Value is also the type of NoSQL database in which data is stored in the form of Key-Value pair. An example of a Key-Value NoSQL database is InfinityDB, Aerospike, Couchbase, Azure Cosmos DB, ArangoDB, MemcacheDB, OrientDB, Berkeley DB, FoundationDB, Oracle NoSQL Database, Apache Ignite, MUMPS, SciDB, ZooKeeper, Dynamo, Redis, SDBM/Flat File dBm, Ria.
What are the features of MongoDB?
MongoDB offers the following list of features.
1. High Performance
MongoDB delivers high performance by supporting the embedded model that reduces the I/O on the database. There is an index key generated for each document that provides fast query processing.
2. Good Query Language
MongoDB provides rich query language support to perform the CURD operations(Read and write) it also supports the data aggregation, text search string operation, Geospatial Queries search to find out the geospatial shapes and points, and so on.
3. High Availability
The replica set features of MongoDB maintain the same data over multiple nodes that are used in case of automatic failover, also replicating the same data sets to multiple nodes helps to achieve the data redundancy, and increases the data availability in case of failure.
4. Horizontal Scalability
MongoDB can scale horizontally based on the workload and the Sharding plays an important role to fulfill this. Sharding will be used to distribute the data over multiple nodes of a cluster for a consistent read and write operation.
5. Multiple Storage Engines Support
MongoDB provides support for different storage engines such as WiredTiger Storage Engine which is the default storage engine for MongoDB that is recommended for new deployments. The second Storage Engine is the In-Memory Storage Engine which is used to store data in memory and used for MongoDB Enterprise.
6. Default Primary Key
Each document in MongoDB has a by default primary key field generated with it.
History of MongoDB
The following is the year-by-year evaluation of MongoDB.
2007: This year the development of MongoDB was started as a 10gen Software Company. The 10gen was founded by Dwight Merriman, Kevin P. Ryan, Eliot Horowitz.
2009: In February 2009, MongoDB was open source by 10gen Software Company.
2010: In August 2010, the first west coast office of 10gen was opened.
2012: In September 2012, the 10gen was recognized as a top 9 software company on the American Business newspaper The Wall Street Journal's The Next Big Thing.
2013: On 27th August 2013, the name of 10gen Software Company was changed to MongoDB Inc.
2014: On 5th August 2014, Dev Ittycheria was named the President and Chief Executive Officer.
2017: On 20th October 2017, MongoDB was listed on NASDAQ and become the public tread company.
2019: On 30th October 2019, MongoDB collaborated with Alibaba to provide the MongoDB-as-a-service solution to its customer.
Difference Between MongoDB and SQL
The below is the difference between MongoDB and SQL.
|Collection||Table and View|
|Primary Key: _ID field||Primary Key: Any column|
|Uniformity is not required.||It has a Uniformity relational Schema.|
|Horizontal Scalability||Vertical Scalability|
|Schema Dynamic||Schema Predefined|
MongoDB Pros and Cons
Let us the implementation of MongoDB in which it is suitable and the implementation in which it is not suitable.
MongoDB Good For
MongoDB is good for the below implementation.
- Product Catalog Management for E-commerce.
- Log generation at high speed.
- Real-time analysis.
- Content Management.
- Blogs Management.
- Geospatial location-based data management.
- Mobile networking.
- Social networking.
- Web Application logging, caching, processing.
- High scalability and load management.
MongoDB Is Not Good For
MongoDB is not good for the below implementation.
- Not suitable for high transaction operation.
- There is no support for the ACID principle.
- The complex SQL in which many joins are present.
- The system in which the data model is developed upfront.
Why do we need MongoDB?
MongoDB is the new era of technology that has succeeded the biggest issue called scalability of the traditional database management system. MongoDB provides a flexible structure that has exceptional scalability and easy to fetch data and support integration. The below are some more reasons mentioned to use MongoDB.
- There is no Downtime needed in the case of Application scalability.
- MongoDB can perform in-memory processing.
- Capable to perform the text-based search operation.
- MongoDB can perform Graph processing.
- It is very Economical.
- Global replication.
MongoDB is a very strong data management platform in today's market and below are some of the strong reasons for that.