Numeric Data: Comparison of NoSQL Databases
By Nathan B. Smith
NoSQL databases were not designed for the same objectives as SQL databases. While SQL was designed to tackle the storage challenges of big, structured datasets, NoSQL solutions were established to solve the storage problems of massive unstructured datasets. Both systems have advantages and downsides.
NoSQL databases provide several benefits when storing, processing, and querying large amounts of data. NoSQL databases are well-suited to high-volume state changes per second and millions of concurrent, dispersed users. In contrast to the norm, NoSQL databases, on the other hand, provide superior sharding and real-time access. Data replication at a reduced cost while maximizing system resources is possible. Relational databases, on the other hand, are excellent for structured data, complicated queries, secure transactions, and a high level of integrity (Redmond & Wilson, 2012).
Because NoSQL solutions are still evolving, they may not be fully mature. Big data engineers and data scientists must carefully pick between NoSQL and relational databases based on their demands in terms of consistency, performance, security, scalability, cost, and other non-functional factors at varying rates.
Different methodologies and criteria may be used to classify NoSQL databases. Data engineers categorize them as key-value, document, column-oriented, or graph based on their data model. The purpose of this post is to compare two representative NoSQL database management systems: Neo4J and CouchDB. Neo4J is a graph database, while CouchDB is a document database (Redmond & Wilson, 2012).
Discussion
Neo4J
Neo4J was developed by Neo4j, Inc. and is in many ways the “elastic band” of databases. It is a system designed not only to store relevant data but to link them and capture their relationships. It is written in Java (“4J”) and Scala. Neo4j belongs to the family of databases known as graph databases since it stores data as a graph. A graph is a collection of linked vertices and edges in this context. Neo4j can store nearly any diagram drawn using boxes and lines (like a UML diagram). Neo4j is more concerned with the relationships connecting values than with the similarities amongst data groups (such as collections of documents or tables of rows). Therefore, it can store vast, diverse data simply and logically. APIs and other access methods used by Neo4J include Bolt protocol, Cypher query language, Java API, Neo4j-OGM, RESTful HTTP, API, Spring Data Neo4j, and TinkerPop 3 (Guia, Soares, & Bernardino, 2017).
CouchDB
CouchDB is a NoSQL database management system developed by the Apache Software Foundation. It is versatile in its ability to scale up and down depending on the scope of the database at hand. It fits nicely into problem areas of various sizes and scopes. CouchDB is the ultimate document-oriented database predicated on JSON (JavaScript Object Notation) and REST (REpresentational State Transfer. CouchDB was created with the web and its countless problems, faults, failures, and hiccups in mind and was released for the first time in 2005. Therefore, CouchDB offers a resilience unmatched by most other databases. In contrast to other systems, CouchDB thrives even when network access is sometimes unavailable.
Like other document-based NoSQL databases such as MongoDB, CouchDB stores documents, which are JSON objects comprised of key-value pairs with values that can be any of a variety of data kinds, including additional nested objects of any depth. Not included, however, is ad hoc querying. Instead, indexed views generated by successive MapReduce processes are the primary means of document discovery. APIs and other access methods include RESTful, HTTP/JSON API (Han, Haihong, Le, & Du, 2011).
Conclusion
Neo4j is the most widely known graph NoSQL database system, designed to capture the relationships between objects as edges linking vertices. Due to its powerful capabilities in capturing relationships, Neo4J is commonly used in fraud detection, 360-degree customer views, AI knowledge graphs, social networks like Facebook or LinkedIn, and supply chain mapping.
CouchDB is a document-based NoSQL database management system that makes sense for synchronizing data in banking, data collecting, log analysis, and the Internet of Things (IoT). The strategy is especially advantageous for businesses with a spread workforce, such as real estate and construction.
References
Guia, J., Soares, V., & Bernardino, J. (2017). Graph databases: Neo4J Analysis. Proceedings of the 19th Conference on Enterprise Information Systems. 1, pp. 351-356. Porto, PT: Science and Technology Publications, Lda. https://doi.org/10.5220/0006356003510356
Han, J., Haihong, E., Le, G., & Du, J. (2011). Survey on NoSQL databases. 6th International Conference on Pervasive Computing and Applications (pp. 363-366). Sydney, AU: IEEE. https://doi.org/10.1109/ICPCA.2011.6106531
Redmond, E., & Wilson, J. R. (2012). Seven databases in seven weeks: A guide to modern databases and the NoSQL movement. Sebastopol, CA: Pragmatic Programmers, LLC, O'Reilly Media.
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