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MongoDB Presentation 
Zain Yousaf
Typical Structured Databasis 
● MySQL 
● SQL 
● Oracle
Problems 
● Difficult to modify schema 
● Difficulty in exchanging data between different 
Databases. 
● Information constrained to schema.
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
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.
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.
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.
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.
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.
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.

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Introduction to mongo db by zain

  • 2. Typical Structured Databasis ● MySQL ● SQL ● Oracle
  • 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.