Automatic Mapping of MySQL Databases to NoSQL MongoDB

Abstract

The paper presents a framework that implements our original algorithm of automatic mapping a MySQL relational database to a MongoDB NoSQL database. The algorithm uses the metadata stored in the MySQL system tables. It takes into consideration the concepts from Entity-Relationship (ER) model: entity type represented by a relation in the Relational Model (RM), 1:1 and 1:M relationship type represented with Foreign Keys (FK) in the RM and N:M relationship type represented in RM with a join table that contains the Primary Keys (PK) from the original tables, each representing a FK and two 1:M relationships between the original tables and the join table. The initial results of our algorithm that was tested on small size databases (10-15 tables with many relationships and 100 records/ table) are presented in this paper.

Transformation of Schema from Relational Database (RDB) to NoSQL Databases

“…There are also several works that proposed transformation of the schema from RDB to document-based NoSQL. In [2], the authors proposed a framework to implement an algorithm that used a metadata stored in RDB for automatic transformation of the entities and association relationships. In [14], the authors used a standalone application named MigDB that analyzes tables in RDB, creates a JSON file based on the tables, and then passing the JSON file to a neural network.…”

“…RDB cannot deal with un-normalized data and massive size, which makes companies like Google, Facebook, and Amazon choose NoSQL database as the option of their data storage [1]. In addition, NoSQL database can support object-oriented paradigm in a better way in comparison to RDB [2].…”

Index data structure, functionality and microservices in thematic virtual museums

“…To store data from crawler service, we are using non-traditional database keyvalue MongoDB for handling structure, semi-structure and unstructured data. There are many advantages of MongoDB as mention in [3][4][5], this type NoSQL document-oriented database using JSON-like format called Binary JSON (BSON), support for partition and MapReduce. MongoDB is using document store model, allow developer to create freeschema, running on multiplatform and opensource.…”

RangeKV: An Efficient Key-Value Store Based on Hybrid DRAM-NVM-SSD Storage Structure

“…P ERSISTENT key-value (KV) stores are an integral part of storage infrastructure in data centers and have been used in many applications including cloud storage [1], online games [2], advertising [3], [4], e-commerce [5], web indexing [3], [6], and social networks [4], [7], [8]. KV stores can be divided into three categories depending on the index structure used: hash index-based design [9], [10], B-tree-based design [11], and log-structured merge (LSM)-tree-based design [12]. Among them, the LSM-tree-based KV stores, such as BigTable [3], Cassandra [13], LevelDB [6], [14], RocksDB [4], and Hbase [15], are state-of-the-art persistent KV stores for write-intensive workloads.…”