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With a data boom in today’s internet age, opting for the right database management system is very important for businesses. Apache Cassandra is a NoSQL database and is readily available, linearly scalable, and provides high performance with variable workloads. It is very ideal for use cases across a wide range of applications such as business and e-commerce applications. Many organizations can use it for their data storage requirements for a specific application. Nevertheless, it is not that good with data analytics as it is not designed for data warehousing and it is not suitable for geographical data management. In this scenario, No-SQL is the best option.
WHERE DOES CASSANDRA EXCEL?
Continuous Availability: You can update the nodes with rolling restarts & accommodate minor outages with any impact on the customer service in a completely distributed database(with no master nodes).
Performance: If you can design the data model aptly by keeping in mind the queries you need to answer, you can get your answers in milliseconds.
Time-series Data: Cassandra is superb when it comes to recording, processing, and retrieving of time-series data.
Apache Cassandra Vs MySQL
TYPE OF DATABASE
Cassandra is a NoSQL database developed by the Apache Software Foundation and was released in 2008. NoSQL(Not only SQL) databases were developed to overcome the shortcomings faced by the Relational Database Management Systems and to cater to the demand of new-age software development. NoSQL databases are capable of supporting a wide range of data that includes documents, key-values, and graph formats. It can store both unstructured and semi-structured data. It adheres to a peer-to-peer architecture.
MySQL, on the other hand, is an open-source Relational Database Management System developed by Oracle. The MySQL databases support related data stored among several tables. MySQL stores structured data in an organized way. The relational model consists of tables (relations) that can be easily interlinked by the keys common to multiple tables. It follows a Master/Slave architecture.
MySQL lends support for vertical scaling. Horizontal scaling is also possible with the aid of a few other approaches like sharding & Master/Slave Replication
To lend support to both horizontal & vertical scaling, Cassandra was developed. Because of the cluster node model, horizontal scaling is also possible. Data can be partitioned easily among different nodes in a cluster.
The way data is modeled is a major difference between Cassandra & MySQL. .
Let us consider a platform where users can post. Now, you have commented on a post of another user. In these two databases, the information will be stored differently. In Cassandra, you can store the data in a single table. The comments for each user is stored in the form of a list(as one single row).
In MySQL, you have to make two tables with one-to-many relationships between them. As MySQL does not permit unstructured data such as a List or a Map, one-to-many relationships are required among these tables.
The query to retrieve the comments made by a user(for example ‘5’) in MySQL, will look like this.
SELECT * from Users u, Comments c WHERE u.user_id=c.user_id and user_id=5;
When you utilize indexing in MySQL, it saves the data like a binary tree.
In Cassandra, it is surprisingly simple:
SELECT * from Users WHERE user_id=3;
You only have to store a single row in Cassandra for a specific user_id. It will require just one lookup.
A search needs to be done with every INSERT/UPDATE/DELETE in MySQL. If you have to update a record with an existing primary key,
- It will first search for the row, and
- Then update it
Cassandra leverages an append-only model. Insert & update have no fundamental difference. If you want to insert a row that comes with the same primary key as an existing row, the row will be replaced. Or, if you update a row with a non-existent primary key, Cassandra will create the row. Cassandra is very fast and stores large swathes of data on commodity hardware without compromising the read efficiency in any way.
MySQL facilitates ACID transactions like any other Relational Database Management System
On the other hand, Cassandra has certain limitations to provide ACID transactions. Cassandra can achieve consistency if data duplication is not allowed. But, that will kill Cassandra’s availability. So, the systems that require ACID transactions must avoid NoSQL databases.
Cassandra excels in a wide variety of applications, especially if you know the model of its data and write your applications accordingly. It is a great choice for time-series data but not a good option for application queues. Cassandra is at its best if you just need to record history and compute from it. MySQL is great for ACID transactions.
The conversation of Cassandra vs MySQL can extend further but it’s your requirement that will help you to choose the best. Share your requirements with Ksolves to get the best out of the difference between Cassandra and MySQL. Our expertise in the Cassandra Consulting Services will ensure that your requirements are kept at priority. Contact us to explore more about the same!
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Advantages of NoSQL over RDBMS: Is the Former a Clear Winner?
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