Ict704 Wildlife Sanctuaries Data Storage Answers


  • Internal Code :
  • Subject Code : ICT704
  • University : University of Sunshine Coast
  • Subject Name : IT Computer Science

Cloud Database Systems

Executive Summary of Wildlife Sanctuaries Data Storage

Recently non-relational database(s) also known as “Not Only SQL” (NoSQL) database is becoming quite popular and gaining popularity for storing organizational data that does not fit the traditional Relational DBMS environment with each having some trade-off. The report critically evaluates the viability of the NoSQL database approach in storing wildlife sanctuaries data and comparison with the traditional RDBMS approach. A brief discussion on some of the available implementation of NoSQL, their advantage, and disadvantages are also presented. Also, This report suggests using non-relational DBMS for some parts of the system while some parts can be used with traditional RDBMS. The report suggests the use of a Hybrid NoSQL/SQL approach to record organization information in a more effective way

Table of Contents

Executive Summary:

Introduction.

1.1 Non-relational databases.

1.2 Key-value.

1.3 Column-oriented.

1.4 Document

Storing Data in NoSQL..

2.1 Scalability and Availability.

2.2 Complexity of Data.

2.3 Structure of data and appropriate data structure.

2.4 Performance.

2.5 Interfacing.

2.6 Security and disaster management

Recommendations.

Conclusion.

References:

1. Introduction to Wildlife Sanctuaries Data Storage

In recent years, various applications have emerged which demands more capability then a traditional database technology can provide such as Low latency highly concurrent read and writes. , Effective storage of Big Data, Scalability and availability, Cost of operations and management, support of big data in search engine. Some of the issues mentioned above cannot be solved by traditional relational database and need a special new type of database(s). NoSQL emerged as a viable option for storing data where the traditional relational database cannot operate that well.

1.1  Non-Relational Databases

A NoSQL provides a mechanism for storage and retrieval of data that does not use traditional tabular relations used in RDBMS. The main advantage of using NoSQL is a quick read and writes, support mass storage, scalability, and low cost. The type of Data model (Atzeni, P. et.al, 2016; Meier, A., and Kaufmann, M., 2019) in NoSQL and some popular platforms that use NoSQL data models are discussed below

1.2 Key-Value

The key-value data model stores values by corresponding them with a key, the implementation is quite simple and speed is higher than RDMS.

1.3 Column-Oriented

Column-oriented database use table but lack table association. Data is stored in a column and each column acts as an index, storing data in column helps in storing similar data and provide a good compression ratio.

1.4 Document

Document database and Key-value is very similar in structure, but the Value of the document database is semantic and is stored in JSON or XML format. It is designed for storing big data with good query performance and trade-off high-performance concurrent read and writes.

2. Storing Data in NoSQL

The case scenario is the use of NoSQL is the storage of data associated with wildlife sanctuaries that need to be evaluated. Here to identify the use case first and divide the system into key components.

2.1 Scalability and Availability

The organization works in different countries that have multiple sanctuaries in several locations some of the locations are South Africa, USA, India, Thailand, etc. RDMS scales well in a multi-server environment but handling tables in multiple servers is very difficult. The database system should support “data sharding” in these cases. Also, the availability of the NoSQL is much better (Mukherjee, S. , 2019) as compared to SQL based database in case of upgrades.

2.2 Complexity of Data

The internal structure of the data in RDBMS is very complex and the mechanism of storing and retrieval also has various overheads. NoSQL might overlook some features of the CAP theorem but provide a very transparent implementation of storing data with high performance and provide finer control in storing data that might not fit a relational structure.

2.3 Structure of Data and Appropriate Data Structure

The key information sources are Countries, Sanctuaries, Staff, Tourist, Booking and accommodations information, Animals Information and their status, etc. which can be transformed into entities and their attributes and can be used in traditional relational DBMS, While some parts of the system are well suited for document type storage.

2.4 Performance

The system should provide mass storage capability but should provide low latencies read and write in our system. The NoSQL system distributes the data into multiple servers for simultaneous operations with distributed loads. RDBMS have overheads such as locking, latching, logging, and buffer management these helps in enforcing data consistencies but performance is hit by these mechanisms. ( Martins, P. et.al. , 2019)

2.5 Interfacing

The biggest advantage of a SQL system is the use of SQL itself for easier interfacing which is considered as the golden standard in the industry. The majority of the RDBMS provides inbuilt GUI which makes it easier to operate. While NoSQL use command line prompt for interfacing and implementation of GUI and interfacing with other application is to be done by Developer itself.

2.6 Security and Disaster Management

The system should handle access control usually SQL database provides security much better than NoSQL but causes performance issues because of back and forth communication overhead with JDBC or ODBC, also using DBMS in an embedded environment compromise the security of the system (Ahmad, K. et.al. , 2019). The security can be implemented in NoSQL but will also introduce overheads, so it is a trade-off between security and performance. Both systems provide some type of disaster management mechanism either by using redundancies or distributed copies in multiple sites.

3. Recommendations on Wildlife Sanctuaries Data Storage

This report suggests using a hybrid approach with the front-end should support SQL based interfacing and scalability of the NoSQL model. It is recommended to use the Hybrid SQL-NoSQL database while combines features of both worlds and provide compatibility with SQL application and scalability of NoSQL (Bjeladinovic, S. et.al., 2020). Some of the platforms to provide this implementation for the organization are

NuoDB (NuoDB, 2020) is a hybrid solution that also provides SQL front-end and ODBC, JDBC, and ActiveRecord drivers is used for application interfacing.it is supposed to run on key-value store. It is deployed in cloud services such as Amazon, Rackspace, etc. It adds a new server to scale the database and the database runs faster. It is ACID-compliant.

VoltDB (VoltDB, 2020) is another hybrid that provides in-memory RDBMS solutions with features such as SQL, ACID support, Hadoop and OLAP integration, great scalability. It is not a DB-as-a-service but a software service for datacentre but it comes in EC2 and WMware images for evaluation in cloud

4. Conclusion on Wildlife Sanctuaries Data Storage

The report suggests the use of a hybrid-approach and implementation of the database in cloud service will help the organization to reduce operational and management costs. It also helps in reducing upgradability issues in the future as the solution will be cloud-based. The hybrid approach helps us to retain the biggest strength of the relational system which is the use of SQL itself which will help in training staff for SQL use much easier as it is a well adopted and mature standard in the industry while the feature of NoSQL will provide great scalability and availability, high performance and finer control on implementation structure. The hybrid approach though is not mature enough and considered as a new platform to provide an attractive solution for the case scenario.

References for Wildlife Sanctuaries Data Storage

Ahmad, K., Alam, M. S. and Udzir, N. I. 2019. Security of nosql database against intruders, Recent Patents on Engineering, UAE, Bentham Science Publishers,13(1), pp. 5-12, DOI: 10.2174/1872212112666180731114714.

Atzeni, P., Bugiotti, F., Cabibbo, L. and Torlone, R. 2016. Data modeling in the NoSQL world. Computer Standards & Interfaces. doi:10.1016/j.csi.2016.10.003 

Bjeladinovic, S., Marjanovic, Z. & Babarogic, S. 2020. A proposal of architecture for integration and uniform use of hybrid SQL/NoSQL database components. Journal of Systems and Software, 110633. DOI:10.1016/j.jss.2020.110633 

Martins, P., Abbasi, M. and Sá, F. 2019. A study over NoSQL performance. New Knowledge in Information Systems and Technologies, pp. 603–611, DOI:10.1007/978-3-030-16181-1_57 

Meier, A. & Kaufmann, M. 2019. Nosql databases. SQL & NoSQL Databases, pp. 201–218. DOI:10.1007/978-3-658-24549-8_7

Mukherjee, S. 2019. The Battle between NoSQL Databases and RDBMS. [Online] Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3393986 [Accessed on 09/09/2020]

NuoDB (2020), NuoDB. [Online] Available at: https://doc.nuodb.com/nuodb/4.0.x/introduction-to-nuodb/ [Accessed on : 09/09/2020]

VoltDB (2020), VoltDB ,[online]Available at: https://docs.voltdb.com/ [Accessed on : 09/09/2020]

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