Bridging SQL and NoSQL Rupal Dhillon U00283533

Introduction In this project, we bring traditional relational databases and non-relational data storage closer together by reducing the developer’s effort required to combine data from both types of databases. Motivated by the recent trend to use non-relational data storage, which leads to separate databases for a single application and the consequential extra work involved with managing multiple data sources.

What is NoSQL? The relational database is the most famous database system. These relational database systems are developed, used, and optimized for decades and offer a solid solution for data storage especially in the area of web applications. Recently a new trend is spotted in web development communities. Besides the traditional relational databases, products like CouchDB, MongoDB, Neo4j, Apache Cassandra, memcached, Redis, JADE, and Apache Hadoop are encountered more often in the context of web development. They are called NoSQL data storage systems.

Definitions SQL : An SQL database is a traditional relational database which can be queried using SQL. NoSQL : A NoSQL database is a database that is not an SQL database. Data is not stored in relations and the main query language to retrieve data is not SQL.

Problem Origin When a single software product requires data storage where a part of the data is ideally stored in a NoSQL database, whereas the rest of the data is perfectly relational and thus well-suited for a traditional SQL database. Raises the question- what type of data storage must be chosen for the application? The obvious compromise is a solution where the relational part of the data is stored in an SQL database, while the non-relational data is stored in NoSQL.

Drawbacks… Scenarios where data from both sources is required. Developers need to access different database systems.

Hybrid Database Abstraction layer on top of the SQL and NoSQL databases. Abstraction layer is responsible for retrieving the relevant data from the underlying SQL and NoSQL databases. Combines the fetched data into a single query result. Desired database abstraction architecture [1]

Approach Separate software layer Load SQL data in NoSQL, either virtual or materialized Load NoSQL data in SQL, either virtual or materialized

Theoretical framework for bridging SQL and NoSQL Architectural workflow illustrating the life of a query [2]

Experimental framework Software: SQL database- PostGRESQL NoSQL database- MongoDB Data : 2 different data sources- Saleable products of a company Twitter data

Conclusion The result of this work is a theoretical framework to bridge SQL and NoSQL. The developer sends a query containing a NoSQL query pattern. This pattern is translated to an equivalent SQL fragment that correctly joins the NoSQL triples retrieved from copies of the triple relation . The triples contained in the relation represent the NoSQL data we wanted to query. The result is a pure SQL query which can be executed like any other query. I have also tried to provide an experimental framework and developed a few ideas which I would like to implement in the near future.

References [1] Roijackers, J., & Fletcher, G. H. L. (2012). Bridging sql and nosql. Master's thesis, Eindhoven University of Technology. [2] Roijackers, J., & Fletcher, G. H. L. (2012). Bridging sql and nosql. Master's thesis, Eindhoven University of Technology.