scholarly journals Comparison and evaluation of state-of-the-art LSM merge policies

2021 ◽  
Author(s):  
Qizhong Mao ◽  
Steven Jacobs ◽  
Waleed Amjad ◽  
Vagelis Hristidis ◽  
Vassilis J. Tsotras ◽  
...  

AbstractModern NoSQL database systems use log-structured merge (LSM) storage architectures to support high write throughput. LSM architectures aggregate writes in a mutableMemTable(stored in memory), which is regularly flushed to disk, creating a new immutable file called anSSTable. Some of the SSTables are chosen to be periodicallymerged—replaced with a single SSTable containing their union. Amergepolicy(a.k.a. compaction policy) specifies when to do merges and which SSTables to combine. Abounded depthmerge policy is one that guarantees that the number of SSTables never exceeds a given parameterk, typically in the range 3–10. Bounded depth policies are useful in applications where low read latency is crucial, but they and their underlying combinatorics are not yet well understood. This paper compares several bounded depth policies, including representative policies from industrial NoSQL databases and two new ones based on recent theoretical modeling, as well as the standard Tiered policy and Leveled policy. The results validate the proposed theoretical model and show that, compared to the existing policies, the newly proposed policies can have substantially lower write amplification with comparable read amplification.

Author(s):  
Harpreet Kaur

NOSql database systems are extremely optimized for performing retrieval and adjoining operations on large quantity of data as compared to relational models which are relatively inefficient. They are used majorly for real-time applications and statistically analyzing the growing amount of data. NoSQL databases emerging in market claim to outperform SQL databases. In Present time of technology, every person wants to save and secure   its data so that no one can check their information without their permission .However, there are multifarious security issues which are yet to be resolved. In this paper, we are discussing and reviewing about the Nosql databases and their most popular security issues link (Cassandra and Mongo DB).


Author(s):  
Omoruyi Osemwegie ◽  
Kennedy Okokpujie ◽  
Nsikan Nkordeh ◽  
Charles Ndujiuba ◽  
Samuel John ◽  
...  

<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>


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zain Aftab ◽  
Waheed Iqbal ◽  
Khaled Mohamad Almustafa ◽  
Faisal Bukhari ◽  
Muhammad Abdullah

Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL database into a structured database. In this paper, we proposed and evaluated an efficient method to transform a NoSQL database into a relational database automatically. In our experimental evaluation, we used MongoDB as a NoSQL database, and MySQL and PostgreSQL as relational databases to perform transformation tasks for different dataset sizes. We observed excellent performance, compared to the existing state-of-the-art methods, in transforming data from a NoSQL database into a relational database.


2019 ◽  
pp. 45-52
Author(s):  
Mohammed Eshtay ◽  
Azzam Sleit ◽  
Monther Aldwairi

NoSQL database systems have emerged and developed at an accelerating rate in the last years. Attractive properties such as scalability and performance, which are needed by many applications today, contributed to their increasing popularity. Time is very important aspect in many applications. Many NoSQL database systems do not offer built in management for temporal properties. In this paper, we discuss how we can embed temporal properties in NoSQL databases. We review and differentiate between the most popular NoSQL stores. Moreover, we propose various solutions to modify data models for embedding bitemporal properties in two of the most popular categories of NoSQL databases (Key-value stores and Column stores). In addition, we give examples of how to represent bitemporal properties using Redis Key-value store and Cassandra column oriented store. This work can be used as basis for designing and implementing temporal operators and temporal data management in NoSQL databases.


2019 ◽  
Vol 13 (2) ◽  
pp. 14-31
Author(s):  
Mamdouh Alenezi ◽  
Muhammad Usama ◽  
Khaled Almustafa ◽  
Waheed Iqbal ◽  
Muhammad Ali Raza ◽  
...  

NoSQL-based databases are attractive to store and manage big data mainly due to high scalability and data modeling flexibility. However, security in NoSQL-based databases is weak which raises concerns for users. Specifically, security of data at rest is a high concern for the users deployed their NoSQL-based solutions on the cloud because unauthorized access to the servers will expose the data easily. There have been some efforts to enable encryption for data at rest for NoSQL databases. However, existing solutions do not support secure query processing, and data communication over the Internet and performance of the proposed solutions are also not good. In this article, the authors address NoSQL data at rest security concern by introducing a system which is capable to dynamically encrypt/decrypt data, support secure query processing, and seamlessly integrate with any NoSQL- based database. The proposed solution is based on a combination of chaotic encryption and Order Preserving Encryption (OPE). The experimental evaluation showed excellent results when integrated the solution with MongoDB and compared with the state-of-the-art existing work.


The chapter explains how NoSQL databases work. Since different NoSQL databases are classified into four categories (key-value, column-family, document, and graph stores), three main features of NoSQL databases are chosen, and their practical implementation is explained using examples of one or two typical NoSQL databases from each NoSQL database category. The three chosen features are: distributed storage architecture that comprises the distributed, cluster-oriented, and horizontally scalable features; consistency model that refers to the CAP and BASE features; query execution that refers to the schemaless feature. These features are chosen because, through them, it is possible to describe most of the new and innovative approaches that NoSQL databases bring to the database world.


The chapter discusses the necessity for data modeling in NoSQL world. The NoSQL data modeling is a huge challenge because one of the main features of NoSQL databases is that they are schema-free, that is they allow data manipulation without the need for the previous modeling or developing an entity-relationship (ER) or similar model. Although the absence of a schema can be an advantage in some situations, with the increase in the number of NoSQL database implementations, it appears that the absence of a conceptual model can be a source of substantial problems. In order to better understand the need for data modeling in NoSQL databases, first the basic structure of an ER model and an analysis of its limitations are summarized, especially regarding an application in NoSQL databases. The concept and Object modeling notation is presented as one of the possible solutions for data modeling in NoSQL databases.


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