Compression & Security in MongoDB without affecting Efficiency

Relational database are not able to deal with Big Data. Hence, to satisfy the demand of emerging Web 2.0 technologies, NOSQL databases are designed. MongoDB, is a schema free, document oriented database. But, it suffers from the problem of authorization, authentication and storing data without encryption. This drawback is overcome by entering data into a middleware before entering into the database. This transparent middleware performs encryption. But, it reduces the efficiency of MongoDB, to store and retrieve data. Instead of providing encryption, this paper came up with a compression technique, to reduce the actual amount of data to be stored. As compression is another form of encryption only. Thus this paper converts plain text into different format of compressed BSON type object. Encryption is achieved this way as data is no more entered in plain format into the database. All this is achieved, without increasing the query execution time of MongoDB. Methodology has been implemented for images also, and verified by calculating the time and number of bytes required to store data before and after compression.

[1]  Kristina Chodorow Scaling MongoDB , 2011 .

[2]  Guan Le,et al.  Survey on NoSQL database , 2011, 2011 6th International Conference on Pervasive Computing and Applications.

[3]  Arpita Gopal,et al.  A study of normalization and embedding in MongoDB , 2014, 2014 IEEE International Advance Computing Conference (IACC).

[4]  Cristian Bucur,et al.  A comparison between several NoSQL databases with comments and notes , 2011, 2011 RoEduNet International Conference 10th Edition: Networking in Education and Research.

[5]  Hans De Sterck,et al.  Supporting multi-row distributed transactions with global snapshot isolation using bare-bones HBase , 2010, 2010 11th IEEE/ACM International Conference on Grid Computing.

[6]  Zhenyu Liu,et al.  Non-structure Data Storage Technology: A Discussion , 2012, 2012 IEEE/ACIS 11th International Conference on Computer and Information Science.

[7]  Arpita Gopal,et al.  Cloud Based Databases- A Changing Trend , 2013 .

[8]  Yong Tang,et al.  Modeling MongoDB with Relational Model , 2013, 2013 Fourth International Conference on Emerging Intelligent Data and Web Technologies.

[9]  Yi Jin,et al.  Research on the improvement of MongoDB Auto-Sharding in cloud environment , 2012, 2012 7th International Conference on Computer Science & Education (ICCSE).

[10]  Wilson C. Hsieh,et al.  Bigtable: A Distributed Storage System for Structured Data , 2006, TOCS.

[11]  E. F. CODD,et al.  A relational model of data for large shared data banks , 1970, CACM.

[12]  Min Wu,et al.  A transparent middleware for encrypting data in MongoDB , 2014, 2014 IEEE Workshop on Electronics, Computer and Applications.

[13]  Frank Dabek,et al.  Large-scale Incremental Processing Using Distributed Transactions and Notifications , 2010, OSDI.