In this article you will understand difference between RDBMS and NoSQL.
RDBMS vs NoSQL
Relational database (RDBMS) is completely structured way of storing data like SQL and has been the primary model for database management during the past few decades and I know most of you already familiar with the SQL database . In the last several years, NoSQL database is getting widely adopted to solve various business problems. So with widely growing DB systems, developer might get confused. In this article I’II show you the difference between them and the evolution.
Relational Database Management System (RDBMS)
RDBMS is completely structured way of storing data. Itis a database management system (DBMS) that is based on the relational model. Data is stored in the form of rows and columns in RDBMS. Data is stored in the form of rows and columns in RDBMS. Some common relational database management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server, Access, etc.
– >Provides data to be stored in tables
– >Persists data in the form of rows and columns
– >Provides facility primary key, to uniquely identify the rows
– >Creates indexes for quicker data retrieval
– >Provides a virtual table creation in which sensitive data can be stored and simplified query can be applied.
– >Sharing a common column in two or more tables(primary key and foreign key)
– >Provides multi user accessibility that can be controlled by individual users
Hardware Performance : Complex queries require sophisticated processing power. Although most desktop computers can manage the databases of the size and complexity often encountered in a small business setting, a database with external data sources or very complex data structures may require more powerful servers to return results within an acceptable response time.
Scalability : Users have to scale relational database on powerful servers that are expensive and difficult to handle. To scale relational database it has to be distributed on to multiple servers. Handling tables across different servers is difficult .
Data Complexity : Data in an RDBMS resides in multiple tables, which are linked to each other through shared key values. An RDBMS does not force database designers to impose a coherent table structure; inexperienced programmers may design systems that create unnecessary complexity or limit the future development of the database through poorly chosen data types. The flexibility of an RDBMS presents a double-edged sword. Experienced designers work magic, but inexperienced designers wreak havoc on a company’s data.
Complexity : In SQL server’s data has to fit into tables anyhow. If your data doesn’t fit into tables, then you need to design your database structure that will be complex and again difficult to handle.
A NoSQL (originally referring to “non SQL” or “non relational”) database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. NoSQL was conceived as a completely different framework of databases that allows for high-performance, agile processing of information at a much bigger scale. This is the database well-adapted to the high demands of big data. The new version of NoSQL runs the database MongoDB, which stores unstructured data.
Why NoSql ?
NoSQL databases are designed to expand transparently and horizontally to take advantage of new nodes, and they’re usually designed with low-cost commodity hardware in mind. For NoSQL, servers can be added or removed from the data layer without application downtime.
No Schema or Fixed Data model
NoSQL database is schema less so Data can be inserted in a NoSQL database without any predefined schema. So the format or data model can be changed any time, without application disruption.and change management is a big pain in SQL.
Lesser Server Cost
NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes while RDBMS databases are expensive and it uses big servers and storage systems. So data processing cost is less in NoSql as comparison to RDBMS.
Integrated Caching Support
In order to increase data output and performance advance NoSQL techniques cache data in system memory. This is in contrast to SQL database where this has to be done using separate infrastructure.
Limitations & disadvantage of NoSQL
NoSQL database is Open Source and Open Source at its greatest strength but at the same time its greatest weakness because there are not many defined standards for NoSQL databases, so no two NoSQL databases are equal.
No Stored Procedures in mongodb (NoSql database) and No Stored Procedures in mongodb (NoSql database).
There are various different limitations to each of them depending on lots of different factors – types of data model (document vs.key/kalue vs. graph, etc), level of persistence (i.e. in-memory only, written to disk), optimal workloads (big table scanning analytics vs. fast random read/write), etc.
However, the biggest limitation / drawback of the first generation NoSQL databases (MongoDB, Cassandra, CouchDB, etc.) is that they lack the ability to perform ACID transactions.
NoSQL over RDBMS
- It support semi-structured data and volatile data
- It does not have schema
- Read/Write through put is very high
- Horizontal scalability is easily achieved
- Will support Bigdata in volumes of Terra Bytes & Peta Bytes
- Good support for Analytic tools on top of Bigdata
- Can be hosted in cheaper hardware machines
- In memory caching option is available to increase the performance of queries
- Faster development life cycles for developers.
For me it’s hard to criticize one and completely go with the other option. RDBMS and NoSQL both are great in data management and both are used to keep data storage and retrieval optimized and smooth. It is better that developer take decision according requirement and situations by considering legitimate limitations associated with these databases.