scholarly journals Active Rules in a Graph Database Environment

10.29007/1w4k ◽  
2020 ◽  
Author(s):  
Ying Jin ◽  
Vadlamannati Bharath ◽  
Jinaliben Shah
Keyword(s):  
Graph Model ◽  
Database Systems ◽  
Graph Database ◽  
Business Logic ◽  
Active System ◽  
Active Rules ◽  
Nosql Databases ◽  
Execution Model ◽  
Relational Database Systems ◽  
Language Specification

With the rapid growth of data nowadays, new types of database systems are emerging in order to handle big data, known as NoSQL databases. One type of NoSQL databases is graph database, which uses the graph model to present data and the relationships among data. Existing graph database systems are passive compared to traditional relational database systems that allow automatic event handling through active rules. This paper describes our approach of incorporating active rules into graph databases, allowing users to specify business logic in a declarative manner. The active system has been built on top of a passive graph database to react to events automatically. Our focus is to specify business rules declaratively rather than enforce integrity constraint using rules. Our system consists of a language framework and an execution model. Language specification will further be illustrated by on a motivating example that shows the use of rules in an application context. The paper also describes the design and implementation of the execution model in detail.

Empirical Evaluation of NoSQL and Relational Database Systems

2020 ◽  
Vol 13 ◽  
Author(s):  
Shivangi Kanchan ◽  
Parmeet Kaur ◽  
Pranjal Apoorva
Keyword(s):  
Empirical Evaluation ◽  
Database Systems ◽  
Memory Usage ◽  
Nosql Databases ◽  
Locking Mechanism ◽  
Relational Database Systems ◽  
Database Operations ◽  
Efficient Memory ◽  
Aggregation Operations ◽  
Aggregate Functions

Aim: To evaluate the performance of Relational and NoSQL databases in terms of execution time and memory consumption during operations involving structured data. Objective: To outline the criteria that decision makers should consider while making a choice of the database most suited to an application. Methods: Extensive experiments were performed on MySQL, MongoDB, Cassandra, Redis using the data for a IMDB movies schema prorated into 4 datasets of 1000, 10000, 25000 and 50000 records. The experiments involved typical database operations of insertion, deletion, update read of records with and without indexing as well as aggregation operations. Databases’ performance has been evaluated by measuring the time taken for operations and computing memory usage. Results: * Redis provides the best performance for write, update and delete operations in terms of time elapsed and memory usage whereas MongoDB gives the worst performance when the size of data increases, due to its locking mechanism. * For the read operations, Redis provides better performance in terms of latency than Cassandra and MongoDB. MySQL shows worst performance due to its relational architecture. On the other hand, MongoDB shows the best performance among all databases in terms of efficient memory usage. * Indexing improves the performance of any database only for covered queries. * Redis and MongoDB give good performance for range based queries and for fetching complete data in terms of elapsed time whereas MySQL gives the worst performance. * MySQL provides better performance for aggregate functions. NoSQL is not suitable for complex queries and aggregate functions. Conclusion: It has been found from the extensive empirical analysis that NoSQL outperforms SQL based systems in terms of basic read and write operations. However, SQL based systems are better if queries on the dataset mainly involves aggregation operations.

scholarly journals Performance Benchmarking of Key-Value Store NoSQL Databases

2018 ◽  
Vol 8 (6) ◽  
pp. 5333
Author(s):  
Omoruyi Osemwegie ◽  
Kennedy Okokpujie ◽  
Nsikan Nkordeh ◽  
Charles Ndujiuba ◽  
Samuel John ◽  
...  
Keyword(s):  
Data Storage ◽  
Web Applications ◽  
Query Language ◽  
Research Work ◽  
Database Systems ◽  
Nosql Databases ◽  
Performance Benchmarking ◽  
Nosql Database ◽  
Structured Query Language ◽  
Web Developers

<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.</p>

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