Cassandra vs. MongoDB vs. Redis vs. MySQL vs. PostgreSQL (Pros and Cons)
Whenever you are working on developing a software application, saving your data is one of the first challenges to be solved. Almost all software applications rely on databases as their foundation. You have to decide which database you want to use.
In this case, we have both SQL and NoSQL databases available for our use. SQL databases, also known as Relational Database Management Systems (RDBMS), have a relational structure, but NoSQL databases don’t. SQL databases are vertically scalable, which implies that they may be run on a single system at a time. Comparatively, NoSQL databases may be accessed by several smaller machines at the same time.
Let’s look at overviews of these SQL and NoSQL databases and their pros and cons.
An open-source NoSQL database, Apache Cassandra or Cassandra, is becoming a popular choice for developers. Cassandra’s ability to handle large volumes of data, scalability, and not having a Single Point of Failure makes it a popular choice.
Cassandra was created by Avinash Lakshman and Prashant Malik on Facebook using Java. In 2008, Facebook made Cassandra available as an open-source project. Cassandra is maintained by the Apache Software Foundation, which is a non-profit organization.
The Advantages of Cassandra
- Decentralization: Unlike other systems, Cassandra does not have a single point of failure. Each node handles the requests in the same way. Hence, if any node fails, data can be easily retrieved from the remaining nodes. Thus, excellent availability is guaranteed.
- Data storage flexibility: Cassandra allows you to store structured, semi-structured, and unstructured data.
- Data distribution flexibility: Cassandra may be set up to use several data centers if you like. This makes it easier to distribute data.
- Performance: If there are many write requests, Cassandra can handle them quickly and efficiently without affecting the read requests.
- Scalability: As data and demands increase, you may quickly add extra hardware to meet those requirements. As a result of this horizontal scalability, you don’t have to shut down the database or make any substantial modifications. Cassandra’s linear scalability assures rapid responsiveness.
- Ease of use: CQL (Cassandra Query Language) is an alternative to SQL that Cassandra offers. Use this simple interface to connect to Cassandra.
The Disadvantages of Cassandra
- Lacks the defining features of RDBMS: There is no relational database management system (RDBMS) in Apache Cassandra. Referential integrity, JOINS, and subqueries like GROUP BY and ORDER BY are not supported by Cassandra.
- Duplication of data: When designing a database using Cassandra, the data is modeled on predicted queries, whereas in an RDBMS, it’s completely different. Thus the data can be duplicated in Cassandra.
- READ operations can be slow: For WRITE operations, Cassandra is incredibly fast. There is a risk of delay if there are too many READ requests sent out.
- Cannot support aggregates: If there are too many aggregate operations Cassandra cannot handle that.
- Limited querying capabilities: Only a restricted number of queries are available in Cassandra for data retrieval purposes.
MongoDB is a NoSQL database that is one of the most popular in the world. It’s a document-based, general-purpose database. Data is stored in JSON-like documents in MongoDB.
The Advantages of MongoDB
- Flexibility: MongoDB has no schemas. Separate documents allow you to store any type of data.
- Sharding: MongoDB supports sharding, which is an effective approach for splitting data into smaller chunks. Data sets of any size can be stored using this technique. You can also divide them over many servers.
- Speed: The ability to index documents in MongoDB allows faster document access, one of MongoDB’s most important advantages.
- Availability: GridFS (Grid File System) is a MongoDB-based file system. It has several helpful features, such as load balancing, replication, and so on. It ensures high availability using these features.
- Scalability: As far as scalability is concerned, MongoDB provides horizontal scaling. In this way, you may divide big datasets over several servers.
- Querying capabilities: MongoDB has powerful querying capabilities. Ad-hoc queries are supported by the system.
The Disadvantages of MongoDB
- Transactional support: Are you developing an application that relies on them? Using transactions, do you plan to change several documents or collections at once? MongoDB does not allow this, and you may encounter corrupt data due to using this method.
- Immature and inadequate “Join” capabilities: This is currently being worked on by developers striving to improve MongoDB. To implement “Joins”, you must create your own code, and it might negatively affect speed.
- A high degree of memory usage: MongoDB’s poor capability for “joins” results in significant memory consumption. Redundancy is created as a result of this. Requires high expertise: To properly deploy indexes, you’ll need the right kind of expertise. As a result, performance might suffer.
- Duplication of data: Since MongoDB is not a relational database management system (Relational Database Management System), duplication of data is caused by a lack of well-defined relationships in the database.
Redis has gained a considerable amount of attention as an open-source NoSQL database. It’s a data structure store that runs in memory. It may be used as a cache, a message broker, or as a database, depending on your needs.
Redis supports multiple data structures. Use it to store strings, hashes, lists, and sets (including sorted sets), bitmaps and geospatial indexes, and more. It is possible to utilize this distributed database as a key-value database that is kept in memory.
The Advantages of Redis
- Excellent for caching: Redis is a great choice for caching. As a result, Redis is more efficient than alternative caching systems.
- Advanced data structures: Redis supports a broad range of advanced data structures, including strings, hashes, lists, sets, etc. Redis has its hashing algorithm, which it calls “Redis Hashing.”
- Flexibility: Redis allows you to store key-value pairs up to 512 MB in size.
- Scalability: You may quickly scale a Redis database without experiencing any downtime or loss in performance.
The Disadvantages of Redis
- Large-scale cloud deployment can be hard.
- A mature clustering solution is not offered.
- “Role-Based-Account-Control” (RBAC) cannot be implemented.
- Lacks in-built encryption.
MySQL is the most widely used relational database management system in the world. This free, open-source solution supports most SQL capabilities. Due to its flexibility and ease of use, MySQL is a popular choice.
The Advantages of MySQL
- Free installation
- Simple syntax and mild complexity
The Disadvantages of MySQL
- Scalability challenges
- Partial open source
- Limited compliance with SQL standards
PostgreSQL is an advanced version of SQL that supports different functions of SQL like foreign keys, subqueries, triggers, and different user-defined types and functions.
The Advantages of PostgreSQL
- Support for custom data types
- Third-party tools integration
- Open-source and community-driven
The Disadvantages of PostgreSQL
- Inconsistent documentation
- Lack of reporting and auditing instruments
In this article, we compared some of the most popular SQL and NoSQL databases. After discussing the pros and cons of MongoDB, Cassandra, Redis, MySQL, and PostgreSQL, we can say that the selection of a database entirely depends on the project requirements and its scalability needs and factors. Therefore, when selecting a database for your project, make sure to fully examine the use cases and technical aspects of your application.