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MongoDB vs Oracle Detailed Comparison

MongoDB is one of the most popular NoSQL databases that use documents in its arrangement, while Oracle is a relational database management system that uses Structured Query Language to maintain data. Both MongoDB and Oracle can be installed and used on all major Operating systems such as Windows, Linux, Unix, etc. An Oracle database is known for databases, tables, and data, whereas a MongoDB is composed of documents in the fields. This article will explain the technical difference between MongoDB and Oracle.

  1. MongoDB Collections vs Oracle Table
  2. Oracle Group By vs MongoDB Aggregate
  3. MongoDB Regular Expressions vs Oracle Regular Expressions
  4. MongoDB Update Document vs Oracle Update
  5. MongoDB Backup vs Oracle Backup
  6. MongoDB Drop Command vs Oracle Drop Command
  7. MongoDB Index vs Oracle Index

MongoDB vs Oracle

MongoDB Collections vs Oracle Table

MongoDB is a grouping of MongoDB documents. In oracle, data is stored in the table while a collection is the equivalent of an RDBMS table. A collection is included in a single database. Collections do not use a schema.

MongoDB Collection

>use test
switched to db test
{ "ok" : 1 }

Oracle Table

CREATE TABLE employee(
    empname VARCHAR2(60) NOT NULL,
    address VARCHAR2(60) NOT NULL,
    PRIMARY KEY(emp_id)

Oracle Group By vs MongoDB Aggregate

In the Oracle database, the GROUP BY clause can be used to group rows by using the values of columns. This clause is one of the most widely used clauses in analytical SQL queries. It returns one row per group and it is used with various aggregate functions like AVG(), MAX(), MIN(), SUM(), and COUNT(). In MongoDB, Aggregations operations use data records and give calculated or computed output. It is used to group values from various documents collectively and can deliver various methods on the distributed data to pass a single output. The Oracle’s count(*) and the group by are an equivalent of MongoDB aggregation.

Oracle Group By Example

SELECT first_id,
       COUNT(*) AS total_rows,
       SUM(sales) AS sales_amount
FROM   product_sales
GROUP BY first_id
ORDER BY first_id;

MongoDB Aggregation Example

> db.testcol.aggregate([{$group : {_id : "$new_employee", emp_value : {$sum : 1}}}])
{ "_id" : "employee", "emp_value" : 2 }
{ "_id" : "113a", "emp_value" : 1 }

MongoDB Regular Expressions vs Oracle Regular Expressions

The Regular expression in the Oracle database can be used with a collection of Oracle SQL functions that enable users to search and handle string data. Regular expressions are an important part of any programming language. In the Oracle database, regular expressions can use various functions in any environment where Oracle Database SQL is used.

Regular Expressions are often utilized in all programming languages. Their job is to hunt for a pattern or word in any string. MongoDB also implements the use of the regular expression for string matching. For this, it uses the $regex operator. MongoDB applies the Perl Compatible Regular Expression as its regular expression language.

MongoDB Regular Expression Example

> db.posts.find({post_text:{$regex:"employee"}}).pretty()
	"_id" : ObjectId("6cc7dr48f1cc4467e2163ft0"),
	"post_text" : "Best employee",
	"tags" : [

MongoDB Update Document vs Oracle Update

The update command or method is present in both relational and non-relational databases. MongoDB uses update() and save() methods to update or manipulate the document into a collection. The update() method modifies the values in the current document and the save() method substitutes the current document with the document declared in save() method. In the Oracle database, the update command is used to update or modify the data from the table. The update command is a part of data manipulation languages. The update method() in MongoDB updates the value present in the document.

MongoDB Update Example

>db.testcol.update({'title':'Physics'},{$set:{'title':'New Physics Topic'}})
WriteResult({ "nMatched" : 2, "nUpserted" : 1, "nModified" : 1 })

Oracle Update Example

UPDATE employee ee
SET    (, ee.address) = (SELECT, dd.address
                                    FROM   dept dd
                                    WHERE =
               FROM   dept
               WHERE  id =;

MongoDB Backup vs Oracle Backup

To take a backup of the database in MongoDB, the mongodump command can be used. This command is used to dump the whole data of the server into the dump directory. This mongodump command can also be used with various options. In oracle, the database backup utility is responsible for backup and restore of the database. Oracle presents the backup utility by giving UI as well as common options.

MongoDB backup example


Oracle Backup Example

  FORMAT '/u01/app/oracle/BACKUP/%d_C_%D_%u_s%s_p%p'
  FORMAT '/u01/app/oracle/BACKUP/%d_D_%T_%u'
  FORMAT '/u01/app/oracle/BACKUP/%d_C_%T_%u'
  FORMAT '/u01/app/oracle/BACKUP/%d_D_%T_%u_s%s_p%p';

MongoDB Drop Command vs Oracle Drop Command

The drop command in MongoDb is used to drop the database and the related indexes completely. This command is one of the most important MongoDB commands as it is responsible for the overall performance and scalability of the database. In the Oracle database, the drop command is used to delete the table from the database or database from the schema. This command is a part of the dynamic definition languages and is used to drop columns from the table too.

MongoDB Drop Example

>use testdb
switched to db testdb
>{ "dropped" : "testdb", "ok" : 1 }

Oracle Drop table example

DROP TABLE employee;

MongoDB Index vs Oracle Index

An index in MongoDB is a specific data structure that contains the data of fields of documents on which the index is built. Indexes increase the activity of search services in the database.

In Oracle and MongoDB, Indexes are responsible for speeding up the search query by giving fast access. Indexes in the relational database management system or non-relational database management system are not always relevant. Indexes are great at reducing the time it requires to search and obtain data using the SELECT statements.

Sometimes index can really decrease the query performance to UPDATE, INSERT, or DELETE. In the Oracle, the index is normally created to get the first or primary set of rows quickly when the table contains too much data in the table. This is responsible for the overall performance of the database.

MongoDB Index Example

"createdCollectionAutomatically" : false,
"numIndexesBefore" : 5,
"numIndexesAfter" : 6,
"ok" : 1

Oracle Index Example

   employee (dno)

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