MongoDB is the most popular database nowadays, used to handle the large data of the website, but there are many databases, used not only to store the data of a website but also to manage it. In this write-up, we will discuss the top competitors of MongoDB by comparing them with it.
What is a database?
A database management system is used to store and manage the data of a website just like a warehouse is used to store the data of any shopping store. A database is of mainly two types either the relational database or a non-relational database, in the relational database the data is stored in tables in an organized way, whereas in a non-relational database, data is stored in a jumbled way, whereas MongoDB is one of the non-relational databases about which we discuss in detail next.
MongoDB
MongoDB is a non-relational database, which follows the BSON model to store data in which data is stored in the form of documents, these documents combine to form the collections and these collections ultimately combine to form a database.
Unlike relational databases, the MongoDB does not follow any definite scheme, rather than that, it follows dynamic schema, in which the user is not bound to define the schema at the time of the creation of a database only, he can define schema at any stage after the creation of a database. This is a great feature as it does not restrict any data to be inserted in the database on the basis of data types.
The most prominent features of the MongoDB are indexing; which enhances the performance of search operations of MongoDB, replication; which allows the data to store its copies in a wide range of servers so that if because of any reason any server crash, its data can be retrieved from any other server, and MongoDB query language (MQL) is used to ad-hoc queries that can be updated on any instant of real-time.
To understand how MongoDB saves the data, let us consider an example of the information about a student which includes its name, age, and city. Let us suppose, we have a student whose name is Paul, 14 years old living in Florida, his information will be stored in MongoDB as:
Name: ‘Paul’
Age: ‘14’
City: ‘Florida’
}
Amazon DynamoDB
As the name reflects, DynamoDB is introduced by Amazon.com and is mostly used for AWS (Amazon Web Services). The DynamoDB is also a NoSQL database which means it is a non-relational database, which follows the document model and key-value structures to store the data in the database.
Amazon DynamoDB does not support any schema and it also supports limited data types rather than a wide range of data types as MongoDB does.
The prominent features of the Amazon DynamoDB are:
- DynamoDB is supported by the AWS Glue Elastic Views which allows the source data to combine and replicate the data of any database with the other databases continuously
- DynamoDB used the PartiQL as its query language to insert, update or delete the data
- DynamoDB also supports the feature to control the prices of AWS products
Comparison between DynamoDB and MongoDB
The general comparison between both of the databases is:
| Parameters | MongoDB | DynamoDB |
|---|---|---|
| Data Model | Supports the JSON document types and BSON document model. Also, it can support documents up to 16 MB in size. | Supports the limited document type and key-value model. Also, it can support documents up to 400 KB in size |
| Query language | It supports rich query language and uses MongoDB query language | It supports key-values queries only and uses PartiQL query language |
| Indexing | Robust, easy to manage, open-source, and indexing produce the latest results | Limited, complex to manage, and can support only 20 GSIs (Global Secondary Indexes) and 5 LSIs (Local Secondary Indexes) |
| Data integrity | 1000 operations per transaction | 25 operations per transaction |
| Pricing | Based on RAM, and storage | Based on the number of inputs |
So if you are going to do a business that is dependent on AWS (Amazon Website Services) then it is recommended you go for Amazon DynamoDB as it will make it easy for you to integrate and maintain your business with the Amazon website services and on the other hand, if your business is independent of AWS then it will be recommended you to go for MongoDB as its features and especially its support to store data in cloud drive will provide great ease in accessing and managing your data.
Microsoft Azure Cosmos DB
Azure Cosmos DB is also a NoSQL database, which is used to store the data of a website and is released by Microsoft as its name indicates.
Microsoft Azure Cosmos DB is a schemaless database, which means there is no restriction of inserting the data depending on the particular data type, and also there is no need to define the data before the creation of the database as relational databases require it.
The prominent features of the Microsoft Azure Cosmos DB are:
- Its response time to the queries is in milliseconds
- It provides enterprise-grade security
- Application development is faster in it
- It provides 25 GB storage free to its new users
Comparison between the MongoDB and Microsoft Azure Cosmos DB
Some basic differences between MongoDB and Microsoft Azure Cosmos DB are:
| Parameters | MongoDB | Microsoft Azure Cosmos DB |
|---|---|---|
| Data model | It stores data in the form of JSON documents | It stores data in the form of documents, key-values, graph DBMS, and wide column storage |
| Cloud-based only | Yes | No |
| APIs and other access methods | Document DB API, GraphDB API, MongoDB API, and Table API | Proprietary protocol using JSON model |
| MapReduce | With Hadoop integration | Yes |
| Maximum document size | 2 MB | 16 MB |
In both of them, MongoDB is preferred by the small business whereas the Microsoft Azure Cosmos DB is preferred by the large business due to the feature of high-level scalability. Moreover, MongoDB only contains the document storage model whereas the Microsoft Azure Cosmos DB contains the storage engines too along with the document storage models.
Couchbase
Northscale is a company that develops a key-value store to save the data of a website, which was known as Memebase and later was renamed as Couchbase Inc.
It uses the semi-structured JSON format to store the data in the database, moreover, it uses the Restful HTTP API, as a query language to insert, modify, and delete the data. The CouchDB follows the two parameters of a CAP theorem which are, Consistency; means all the clients associated with it should contain the same type of data, and another one is Partition tolerance; means if the communication between the nodes breaks down, the database cluster will still be working.
The prominent features of the Couchbase are:
- Couch supports both; master-slave and master-master replication
- Couchbase servers perform different roles on a single or multiple nodes like security, replication, and data service
- Couchbase obeys three rules; Memory-first high-performance design, asynchronous approach to all the tasks, and workload isolation
Comparison of Couchbase and MongoDB
The basic comparison of both, Couchbase and MongoDB are:
| Parameters | MongoDB | Couchbase |
|---|---|---|
| ACID transactions | Unlimited | Limited |
| Compatibility with shred key | Yes | No |
| Handling capacity | It cannot handle multi documents easily | It can handle multi documents easily |
Both are very popular depending on their own specifications like MongoDB is very much recommended for applications where the structure is not predefined, on the other hand, couchbase can provide high availability using its features like index replication.
PostgreSQL
PostgreSQL is an RDMS that is used to manage data of relational databases, stored in the form of tables. The data inserted is dependent on the schema which is designed before the creation of the table so the data inserted in the database should follow that schema strictly.
Along with the relational database, it also supports the JSON document model, which means it responds to the NoSQL queries as well. PostgreSQL is used for many mobile applications and analytical applications.
The prominent features of PostgreSQL are:
- It has the ability of inherited tables
- It allows asynchronous replication
- It is extensible as it allows users to define their own data types and functional languages
Comparison of MongoDB with PostgreSQL
The main parameters of comparison between MongoDB and PostgreSQL are:
| Parameters | MongoDB | PostgreSQL |
|---|---|---|
| Description | It is a non-relational database management system | It is a relational database management system |
| Developed in languages | C, C++, and Javascript | C |
| Orientation | Document oriented | Object-oriented |
| Multilingual | No | Yes |
If you are going to manage hundreds of documents then it will be better to use MongoDB as it contains a high processing speed than PostgreSQL, because it can use a horizontal scaling approach. On the other hand, if you have to establish the relationship between the tables, it will be better to use the PostgreSQL database.
Redis
In 2009, Salvatore Sanfilippo developed the Redis which is known as a purpose-built database, which means it needs some static memory to store the data because it has no server where its data can be stored. It also has the feature of using the persistent data structure by which the users can perform complex tasks with excellent performance.
The unique feature of Redis is that it supports the “Lua script”, due to which it is known as an intelligent cache; so it can be used for high computations.
It stores the data in the form of key-value in documents that are well structured. To understand the key-values, consider an example of a data Name= John, here “Name” is the key, and “John” is the value.
Now, if we talk about the more features of the Redis, then,
- It has flexible data structures
- It allows replication
- It provides the best performance by supporting the caches
Comparison between MongoDB and Redis
The comparison between the Redis and MongoDB is:
| Parameters | MongoDB | Redis |
|---|---|---|
| Primary database model | Document-based | Key-value |
| Secondary database model | Spatial DBMS, time-series DBMS, and Search engine | Document store, Graph DBMS, Spatial DBMS, and Search engine |
| Typing | Yes | Partial |
| SQL | Read via SQL queries only | No |
| API’s | Proprietary protocol using JSON | Proprietary protocol |
| Server-side scripts | JavaScript | Lua scripts |
| Map-reduce | Yes | Through Redisgears |
| Performance | It can not handle a large volume of workload easily | It can handle a large volume of workload |
Redis can be used in companies where troubleshooting is not an important factor whereas, in companies in which performance is considered strictly, MongoDB will be recommended. Similarly, MongoDB is very much easy to use as compared to Redis, likewise, if you are going to handle a lot of queries, MongoDB will be better than Redis because of its simple JSON document model.
Cassandra
Cassandra was launched in 2008 by Google, in 2009 it became a part of an incubator project and later on, in 2010 it was known as the top-level project of the database. Cassandra is an open-source database management system that is used to manage the data of NoSQL databases in the form of a cluster model.
It can manage a huge data as it is following the cluster model, in which data is distributed among a number of nodes, each node is having different data but all are interlinked with other nodes as well so in case of any node crash down, the data is secure and can be retrieved from any other node.
The prominent features of Cassandra are:
- It replicates the data among multiple data centers so that it ensures that on the failure of any node it can replace with any other node
- To ensure stability and reliability it is gone through a lot of testings such as fault-injection tests, performance tests, and property-based tests
- The data is distributed among many nodes so it can retrieve from any node
- The databases can be modified at any instant of time without interrupting the applications
Comparison between the MongoDB and Cassandra
The comparison between the MongoDB and Cassandra are:
| Parameters | MongoDB | Cassandra |
|---|---|---|
| Data availability | If master nodes fail down, the slave node take place of the master node, but it takes some time | It replicates the data among different nodes so, in the case of failure of a node, data is still secure |
| Scalability | The master nodes only are capable of modifying and accepting the data, where slave nodes can only read the data | It has multiple master nodes, so can enhance the scalability by executing different tasks using multiple master nodes |
| Data Model | Document model | Table model |
| Schema | Does not require any schema | It needs a schema |
On the basis of the query, if it depends on the primary index then Cassandra will be recommended and if it is a secondary index then MongoDB will be preferred.
Conclusion
Databases are used to store the data of websites, either in relational databases or NoSQL databases, the most popular database which is used nowadays is MongoDB, though there are different other databases too like Amazon DynamoDB, Microsoft Azure Cosmos DB, Couchbase, PostgreSQL, Redis, and Cassandra which are also equally popular. All these databases have their own features on the basis of which they have unique applications. In this writeup, we have discussed MongoDB and the features of the databases which can be considered as its competitor. We have also discussed a precise comparison of MongoDb with each of its competitors.
