SQL vs NoSQL vs NewSQL
Adapting to the changing requirements, database management systems pursues to evolve. In this blog, I will show you the prominent difference between SQL vs. NoSQL vs. NewSQL.
Sometimes back NoSQL was solution to the limitations initiate by the relational database management systems. NoSQL was originally designed to provide fast scalability when dealing with unstructured data platforms or handle Big Data applications. But with the dramatic change of the requirements, the major drawbacks discussed below was identified. That is where NewSQL stole the spot light. NewSQL is a relational database with the scalable properties of NoSQL which is the latest development in the world of database systems
What is SQL Relational Database?
The SQL, or Structured Query Language, is the standard query language for interacting with a relational database management system. From an external viewpoint, this means data is viewed as tables of rows and columns using a fixed schema, meaning each row has the same columns defined using the same data types as every other row in a table.The key features behind SQL relational databases are
- ACID property to maintain the reliability of transactions
- Normalization — A process of designing efficient databases
- Vertical scalability
Why SQL was not enough?
As data volume has grown over the past few decades, SQL databases have struggled with particular use cases driven by big data requirements. Some of the significant reasons were listed below.
- Explosion of social media sites with large data needs.
- Rise of cloud-based solutions.
- Shift to dynamically-typed data with frequent schema changes.
- Expansion of Open-source community.
- Handle big data.
What is NoSQL?
NoSQL database simply stands for “Not Only SQL” or “Not SQL. The original NoSQL systems were built for scale, unstructured data, and did not use relational (table-based) schema.
- Key-value databases store pairs of unique keys and associated values. Ex:- Redis
- Document databases store data in document-like structures encoded in formats such as JSON and XML. Ex:- MongoDB
- Wide-column databases store data in tables that contain large numbers of columns (in a flexible schema). Ex:- Cassandra
- Graph databases store data in graph form to highlight the connections between different data elements. Ex:- Neo4j.
The key features of NoSQL are as follows.
- Lack of schema
- The BASE Principle — The base stands for Basically Available Soft-state, Eventually consistent.
- Horizontal scalability
Why SQL and NoSQL was not enough?
- NoSQL databases have limited query capabilities as compared to RDBMS.
- NoSQL databases don’t offer any RDBMS capabilities like consistency and ACID transactions.
- Most of the NoSQL databases use key-value pairs to store the data. Hence it isn’t easy to maintain as the volume increases.
- NoSQL databases are new to the markets and can be challenging for RDBMS programmers to switch to these technologies.
- Most of the NoSQL databases are open source and are a restricted choice for enterprises.
What is NewSQL?
NewSQL, is a class of modern relational DBMS that provides the same scalable performance of NoSQL systems for online workloads but also provides ACID so as to not sacrifice data consistency. The term was first used by 451 Research in a 2011 research paper discussing the rise of new database systems as challengers to established vendors.
Basically, a NewSQL DBMS is engineered as a relational, SQL database system with a distributed, fault-tolerant architecture. Other typical features of NewSQL offerings include in-memory capability and clustered database services with the ability to be deployed in the cloud.
The general use case for NewSQL is to support enterprise systems that must process large amounts of data (big data) while maintaining transactional consistency and are, therefore, not practical for the eventual consistency of NoSQL database systems.
Key features of NewSQL:
- Main Memory storage of OLTP databases enables in-memory computations of databases.
- Scaling out by splitting a database into disjoint subsets called either partitions or shards, leading to the execution of a query into multiple partitions and then combining them into a single result.
- NewSQL systems preserve the ACID properties of databases.
- Enhanced concurrency control system benefits traditional ones.
- Presence of a secondary index allowing NewSQL to support faster query processing times.
- High availability and Strong data durability only possible with the use of replication mechanisms.
- Configure NewSQL systems to provide synchronous updates of data over the WAN.
- Minimizes Downtime, provides fault tolerance with its crash recovery mechanism.
Difference Between SQL, NoSQL, and NewSQL
Which is the Best Solution: SQL or NoSQL or NewSQL?
After reviewing the basics of each type of database system, Now I know that you expect me to answer this question… But the choice is totally up to the requirement that you have.
It makes sense to use SQL database systems as the baseline for most general-purpose requirements. There is a reason the SQL DBMS is as popular and entrenched as it is: It works very well for many of the most common use cases.
For applications with extreme availability and scalability needs or with unknown or changing data requirements where a flexible schema would be useful, consider a NoSQL database system. But take heed of the potential for data consistency issues and realize that NoSQL is a term that describes four different types of database systems, each with different use cases and architectures.
Finally, consider a NewSQL database system for applications that have expanded past the scalability capability of traditional SQL. Using NewSQL enables improved scalability with the strong transaction consistency of ACID, while still supporting data access using the familiar SQL.
Happy reading!!! Bye until next time :)