Updated February 28, 2023
Difference Between RDBMS vs NoSQL
The relational database management system is designed for relational databases to provide data in rows and columns or in a properly structured format. The database is provided digitally for the relational model of data. Data is stored in tables and have an identifier. This identifier called the primary key is used to connect with other tables. The database used for storing and retrieving data in other means rather than with a primary key is called NoSQL. A proper schema is not needed to insert data into the database. Hence the changes can be made faster.
Head to Head Comparison between RDBMS vs NoSQL (Infographics)
Below are the top 8 differences between RDBMS vs NoSQL:
Key Differences
Following are key differences between RDBMS vs NoSQL:
- RDBMS is called relational databases while NoSQL is called a distributed database. They do not have any relations between any of the databases. When RDBMS uses structured data to identify the primary key, there is a proper method in NoSQL to use unstructured data.
- RDBMS is scalable vertically and NoSQL is scalable horizontally. Hence in RDBMS, servers have to be added and power has to be increased. This makes scalability an RDBMS expensive. While in NoSQL, we just need to add more machines and this does not make the database expensive.
- Maintenance of RDBMS is expensive as manpower is needed to manage the servers added in the database. NoSQL is mostly automatic and does some repairs on its own. Data distribution and administration is less in NoSQL.
- As stated earlier, RDBMS is expensive due to the servers and storage management. NoSQL databases are open source and cheap when compared with RDBMS. Servers in NoSQL can be used to manage and transact data with relatively no cost at all.
- RDBMS has a fixed schema so that data has to be inserted in a proper format. This helps to get the primary key and foreign key to align the data in the table. Primary keys help to connect the data from other tables with the common identifier. But in NoSQL, a schema is not needed and hence data can be inserted in any form. Also, these data can be inserted at any time and updates can be made without any prior notice. This helps the database to work flexibly with the users.
- Data output performance is better in NoSQL due to the support caching in system memory. Separate infrastructure is not needed and hence this makes the developers tally the data easily. Whereas in RDBMS, separate infrastructure is needed due to the absence of support caching. This makes the data tally difficult.
- NoSQL data structure is never equal due to the absence of schema and the fact that it is open source. This makes the database be without a proper standard. RDBMS has a proper schema and data has to be inserted only in the given format. The data structure is equal from one table to another.
- RDBMS has stored procedures to understand the data and to know them well. NoSQL, however, does not have any stored procedure. This makes it difficult for users to identify the pattern and to learn the data well.
RDBMS vs NoSQL Comparison Table
Let us discuss the top comparison between RDBMS vs NoSQL:
| RDBMS | NoSQL |
| Users know RDBMS well as it is old and many organizations use this database for the proper format of data. | This is relatively new and experts in NoSQL are less as this database is evolving day by day. |
| User interface tools to access data is available in the market so that users can try with all the schema to the RDBMS infrastructure. This helps to interact with the data well and users will understand the data in a better manner. | User interface tools to access and manipulate data in NoSQL is very less and hence users do not have many options to interact with data. |
| RDBMS scalability and performance faces some issues if the data is huge. Servers may not run properly with the available load and this leads to performance issues. | It works well with high loads. Scalability is very good in NoSQL. This makes the performance of the database better when compared with RDBMS. A huge amount of data could be easily handled by users. |
| Multiple tables can be joined easily in RDBMS and this does not cause any latency in the working of the database. The primary key helps in this case. | Multiple tables cannot be joined in NoSQL as it is not an easy task for the database and does not work well with the performance of the data. |
| The availability of the database depends on the server performance and it is mostly available whenever the database is opened. The data provided is consistent and does not confuse users. | Though the databases are readily available, consistency provided in some databases is less. This results in the performance of the database and users should check the availability often. |
| Data analysis and querying can be done easily with RDBMS even though the queries are complex. Slicing and dicing can be done with the available data to make the proper analysis of the data given. | Data analysis is done also in NoSQL but it works well with real-time data analytics. Reports are not done in the database but if the application has to be built, then NoSQL is a solution for the same. |
| Documents cannot be stored in RDBMS because data in the database should be structured and in a proper format to create identifiers. | Documents can be stored in the NoSQL database as this is unstructured and not in rows and columns format. |
| Partitions cannot be created in the database. Key-value pairs are needed to identify the data in a particular format specified in the schema database. | Partitions can be created in the database easily and key-value pairs are not needed to identify the data in the source. Software as a service can be integrated with NoSQL. |
It is better to select the database based on the requirement and availability of data in the server. Experts are needed for both the databases to manage and work with it. Reports and applications can be developed in the databases and these help the users to find the relevant data in the server.
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