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Storage and databases for big data
Published in Jun Deng, Lei Xing, Big Data in Radiation Oncology, 2019
Tomas Skripcak, Uwe Just, Ida Schönfeld, Esther G.C. Troost, Mechthild Krause
MongoDB is one of the most popular JSON-oriented document databases that have been released under the open-source license. Internally, it uses the binary-encoded format called BSON. The BSON format extends the JSON specification about low-level representation of data types such as Dates and allows document parsing operations to be much more efficient. MongoDB utilizes JavaScript as a special-purpose query language that can be used to perform ad hoc queries on document collections and for execution of user-defined functions on the server side. It is known for its developer friendliness that allows quick entry into to world of big data technologies; however, it does not currently provide the best robustness and scalability. Furthermore, the utilization of JavaScript makes MongoDB vulnerable to NoSQL injection attacks discussed in the following section. Even considering these flaws, MongoDB could be a good candidate for big data prototyping scenarios. However, in its present state, it is not a best choice for sustainable productive big data infrastructure in translational radiation oncology research.
Performance of serial and parallel processing on online sentiment analysis of fast food restaurants
Published in Shin-ya Nishizaki, Masayuki Numao, Jaime Caro, Merlin Teodosia Suarez, Theory and Practice of Computation, 2019
B. Quijano, M.R. Nabus, L.L. Figueroa
MongoDB is a document-oriented DBMS that manages “documents” i.e. a set of key-value or key-array pairs that can be semi-structured, unlike records in relational DBMSs. Its documents are stored in a Binary JavaScript Object Notation (BSON) format (MongoDB Inc., 2017), which allows it to store data that make use of the JSON format as is, such as raw data streams provided by Twitter APIs (Twitter Inc., 2017). Previous research studies such as the ones done by Oliveira et al. (2013) and Bing et al. (2014) have used MongoDB to store Twitter data for their sentiment analysis studies on Twitter sentiments and stock price correlation.
Are NoSQL Databases Affected by Schema?
Published in IETE Journal of Research, 2023
Neha Bansal, Shelly Sachdeva, Lalit K. Awasthi
MongoDB stores data in a binary format called BSON, which is “Binary JSON.” BSON is a flexible, efficient, easy-to-parse binary representation of JSON-like documents. In MongoDB, data is stored in collections, analogous to tables in a relational database. Each document in a collection is a BSON object that can contain multiple fields, including nested objects and arrays. Documents are not required to have a fixed schema, so different documents in the same collection can have various fields. MongoDB uses a flexible indexing system to optimise query performance. By default, every collection has a primary index on the _id field, a unique identifier for each document. MongoDB also supports a wide range of secondary indexes, including indexes on nested fields and multi-key indexes on arrays. MongoDB does not support joins and offers to embed or reference data instead of joins. The logical representation of MongoDB is given in Figure 1.
Smart city data architecture for energy prosumption in municipalities: concepts, requirements, and future directions
Published in International Journal of Green Energy, 2020
Furthermore, data layer stores processed energy data from metering devices, energy sensors, etc. in MongoDB database as suggested by Zabasta et al. (2018). MongoDB is opted as a good choice for storing JSON encoded data as it internally retains data in a well-organized binary JSON format (BSON) (Zabasta et al. 2018). This layer also stores Metadata, which refers to the tags or descriptors that classify a document, dataset, data model, or data source (Tcholtchev et al., 2017). The metadata information is automatically generated by data processing system based on a standard of DataCite Metadata Schema and serves as a link to isolated data and aids data fusion in smart cities (Liu et al. 2017).
Big Data Retrieval Using Locality-Sensitive Hashing with Document-Based NoSQL Database
Published in IETE Journal of Research, 2021
N.R. Gayathiri, A.M. Natarajan
MongoDB is a document-oriented, cross-platform database that offers over the top execution, high accessibility, and programmed scaling. It is easy to build MongoDB’s document model as it bolsters unstructured data. When the application necessities changes, time-consuming relocations need not be embraced. MongoDB’s data stored as archives are encoded in a JSON-like format, called as BSON, that makes storing simple, is a characteristic counterpart for the current object-orientated programming techniques, and is in like manner lightweight, fast, and safe [12].