Proceedings ArticleDOI
NoSQL databases: Critical analysis and comparison
Reads0
Chats0
TLDR
The comparison between MongoDB, Cassandra, Redis and Neo4j concluded that all of them follow horizontal scaling and are schema free, except Neo4J, which doesn't have complete ACID properties.Abstract:
The current research explores and differentiates between various forms in which NoSQL databases exist. It examines the need of NoSQL and how they have become an important alternative to relational databases. NoSQL databases can be categorized into four major classifications which are: key value stores, graph databases, wide column stores, and document stores. These categories are compared on the basis of functional features and non-functional features. The non-functional features include performance, scalability, flexibility, structure and complexity. The functional features include de-normalization, joins, atomicity, aggregation and keys. Then for further analysis, one database is selected from each of these categories that is, MongoDB (document stores), Cassandra (wide column stores), Redis (key value stores), and Neo4j (graph databases). Selected databases are compared on their data model, CAP theorem, distributive properties and other factors. By performing the comparison on non-functional features, it has been found that a document store can be used if high performance, flexibility and scalability are required and if we have represented the data in JSON format. Column store can be used for semi structured data which requires high performance and scalability. Redis is anin-memory store and performs exceptionally fast in the case of single shard operation. Graph databases can be used when it comes to highly interconnected data and continuously evolving data models. The comparison between MongoDB, Cassandra, Redis and Neo4j concluded that all of them follow horizontal scaling and are schema free. Except Neo4j, others don't have complete ACID properties. Write and delete operations are fast for databases MongoDB, Redis and Cassandra, whereas read operation is comparatively slow in Cassandra. In case of Neo4j, REST performance is similar to MongoDB, whereas embedded is comparatively slow. We also discuss how these databases work in a distributed environment.read more
Citations
More filters
Journal ArticleDOI
Algorithms for frequent itemset mining: a literature review
TL;DR: This paper reviews and presents a comparison of different algorithms for Frequent Pattern Mining (FPM) so that a more efficient FPM algorithm can be developed.
Proceedings ArticleDOI
A Framework to Convert NoSQL to Relational Model
TL;DR: A generic framework is proposed in this paper so that different NoSQL databases could be converted to RDBMS, and a case study on MongoDB and Neo4j proves robustness of the proposed mechanism.
Book ChapterDOI
Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks
Ogerta Elezaj,Sule Yildirim Yayilgan,Edlira Kalemi,Linda Wendelberg,Mohamed Abomhara,Javed Ahmed +5 more
TL;DR: A knowledge graph-based framework is presented, an outline of a framework designed to support crime investigators solve and prevent crime, from data collection to inferring digital evidence admissible in court.
Patent
Data processing method and apparatus for KV engine
TL;DR: In this article, the authors present a data processing method and apparatus for a KV engine, which comprises the steps of obtaining information source data, and preprocessing the information sources data to obtain to-be-stored data; checking the data stored in the KVM engine, and if the check is passed, storing the data in the engine by adopting different KEYs according to a data storage mode of an information invasion index.
Journal ArticleDOI
Increasing Security of Database During Car Monitoring
TL;DR: In this paper, the authors proposed effective data distribution methods and a mechanism for data transfer from a database to data storage according to individual records' time parameters, which can lead to a wrong decision about a transport situation prediction task, inaccurate result in decision support, or even to lousy diagnosis prediction.
References
More filters
Proceedings Article
Bigtable: A Distributed Storage System for Structured Data (Awarded Best Paper!).
Fay W. Chang,Jeffrey Dean,Sanjay Ghemawat,Wilson C. Hsieh,Deborah A. Wallach,Michael Burrows,Tushar Deepak Chandra,Andrew Fikes,Robert Gruber +8 more
TL;DR: Bigtable as mentioned in this paper is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers, including web indexing, Google Earth and Google Finance.
Journal ArticleDOI
Bigtable: A Distributed Storage System for Structured Data
Fay W. Chang,Jeffrey Dean,Sanjay Ghemawat,Wilson C. Hsieh,Deborah A. Wallach,Michael Burrows,Tushar Deepak Chandra,Andrew Fikes,Robert E. Gruber +8 more
TL;DR: The simple data model provided by Bigtable is described, which gives clients dynamic control over data layout and format, and the design and implementation of Bigtable are described.
Journal ArticleDOI
Cassandra: a decentralized structured storage system
Avinash Lakshman,Prashant Malik +1 more
TL;DR: Cassandra is a distributed storage system for managing very large amounts of structured data spread out across many commodity servers, while providing highly available service with no single point of failure.
Journal ArticleDOI
Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services
Seth Gilbert,Nancy Lynch +1 more
TL;DR: In this paper, it is shown that it is impossible to achieve consistency, availability, and partition tolerance in the asynchronous network model, and then solutions to this dilemma in the partially synchronous model are discussed.
Journal ArticleDOI
Scalable SQL and NoSQL data stores
TL;DR: This paper examines a number of SQL and socalled "NoSQL" data stores designed to scale simple OLTP-style application loads over many servers, and contrasts the new systems on their data model, consistency mechanisms, storage mechanisms, durability guarantees, availability, query support, and other dimensions.