3. Problems
● Difficult to modify schema
● Difficulty in exchanging data between different
Databases.
● Information constrained to schema.
4. Solution
● Remove constraints on data
● No defined size of data records.
● No defined fields of a data record
● Remove dependencies of tables.
In easy words
Remove Schema
5. Document Oriented Database
A document oriented database is defined as
● It can represent the information of some data sources that
cannot be constrained by schema.
● It provides a flexible format for data exchange between
different types of databases.
● It can be helpful to view structured data as semi-structured
(for browsing purposes).
● The schema can easily be changed.
● The data transfer format may be portable.
6. MongoDB
● Document Oriented Database has numerous
instances but here we will discuss the
MongoDB. It was
● Developed by 10gen (now MongoDB Inc.)
● Written in C, C++, JavaScript.
● is now being used by Brave Collective, Craigslist, eBay,
Foursquare, SourceForge, Viacom, and the New York
Time.
7. MongoDB
In MongoDB,
● Tables become collections
● Records become documents.
● Documents are JSON like arrays
● Collections are arrays of documents.
● Just like JSON, documents can be and
contain multi-dimensional arrays.
8. Features
● Document oriented.
● Ad-hoc Queries: search by field, range queries, regular expression
searches.
● Any field can be indexed.
● Can run on multiple servers duplicating data to keep the system up
and running in case of hardware failure.
● Can behave like a complete file system.
● MapReduce can be used for batch processing of data and
aggregation operations
● JavaScript command can be written and sent to server directly
● Can maintain capped collection which behaves as circular queue
after certain size.
9. limitations
● Reader-writer-lock allows multiple read
operations and one write operations.
● Works good with 64-bit systems and poses
some limitations with 32-bit system.
● Does not provide correct ordering with non-
English languages.
10. Applications
● Efficient for big data as there are no
dependencies between data. Thats why above
mentioned websites have shifted to it.
● Very compatible to be used in REST-ful API
due to JSON structure of documents.
