Cassandra vs. MongoDB
Data makes today’s world go round. This is the age of mobile devices, wireless networks, and the Internet of Things. Data is everywhere, from your everyday working world to your leisure time, and everything in between.
It’s easy to get overwhelmed by massive data volumes, so there are many tools designed to make the information more manageable. But which is best? Today we will be looking at two database management systems: Cassandra vs. MongoDB. This article will shine a spotlight on both systems, including their advantages and disadvantages, and help you recognize the difference between Cassandra vs. MongoDB.
But before we check out the differences between MongoDB and Cassandra, let’s refresh ourselves with the fundamentals.
What Is a Database Management System?
Database management systems (DBMS) are software solutions used to store, retrieve, manage, and define data in a database. A DBMS enables end-users to create, delete, read, and update the data in a database.
A sound database management system offers the following benefits:
- Provides security and eliminate redundancy
- Supports multiple views of the data
- Allows data sharing and multi-user transaction processing
- Follows the ACID concept (Atomicity, Consistency, Isolation, and Durability)
- Supports multi-user environments that allow users to access and manipulate data in parallel
What Is Cassandra?
Apache Cassandra is an open-source NoSQL database management system known for its high availability and scalability, Cassandra can handle massive amounts of data and provide real-time analysis. Unlike traditional databases, NoSQL databases like Cassandra don’t require schema or a logical category to store large data quantities.
Cassandra is written in Java and open-sourced in 2008. Organizations and companies like AppScale, Constant Contact, Digg, Facebook, IBM, Instagram, Spotify, Netflix, and Reddit favor it.
If you want to know more about and how to learn Cassandra, check out this Cassandra tutorial.
What Are the Advantages of Cassandra?
When considering Cassandra vs. MongoDB, see this list of reasons why Cassandra is a solid database management choice:
- It’s open-source
- It follows peer-to-peer architecture rather than master-slave architecture, so there isn’t a single point of failure
- Cassandra can be easily scaled down or up
- It features data replication, so it’s fault-tolerant and has high availability
- It’s a high-performance database manager that easily handles massive amounts of data
- It’s schema-free (or, schema-optional), so you can create your columns within the rows, and there is no need to show all the columns required to run the application
- It supports hybrid cloud environments since Cassandra was designed as a distributed system to deploy many nodes across many data centers
What Are the Drawbacks of Cassandra?
Naturally, no database management tool is perfect. Here are Cassandra’s downsides:
- It doesn’t support ACID and relational data properties
- Because it handles large amounts of data and many requests, transactions slow down, meaning you get latency issues
- Data is modeled around queries and not structure, resulting in the same information stored multiple times
- Since Cassandra stores vast amounts of data, you may experience JVM memory management issues
- It offers no join or subquery support
- Cassandra doesn’t support aggregates
- Cassandra was optimized from the start for fast writes, reading got the short end of the stick, so it tends to be slower
- Finally, it lacks official documentation from Apache, so you need to look for it among third-party companies
What Is MongoDB?
Like Cassandra, MongoDB is an open-source NoSQL database management system. Its architecture relies on documents and collections instead of rows and tables. It’s highly scalable and ideal for real-time analytics and high-speed logging.
MongoDB was created in 2007 by the DoubleClick design team to work out agility and scalability issues associated with serving DoubleClick’s internet ads. It’s a schema-less database that stores data as JSON-like documents, providing data records with agility and flexibility. MongoDB is written in C++, Go, JavaScript, and Python.
MongoDB has a community and an enterprise version, with the latter offering extra features like auditing, Kerberos, LDAP, and on-disk encryption. IT professionals use MongoDB for content management systems, IoT applications, mobile applications, and whenever you want a real-time view of your data. Companies like Adobe, BOSH, Cisco, eBay, Facebook, Forbes, Google, SAP, and UPS use MongoDB.
If you’re interested in learning more about MongoDB, click on this MongoDB tutorial.
What Are the Advantages of MongoDB?
To get a better understanding of Cassandra vs. MongoDB, let’s look at the pros MongoDB offers, such as:
- Provides support for in-Memory or WiredTiger storage systems
- It’s flexible and agile thanks to its schema-less database architecture
- It offers a deep query capability, which supports dynamic document queries using a dedicated language that is almost as powerful as SQL
- It scales easily
- You can index any attribute
- You don’t need to map or convert application objects into database objects
- It accesses data faster thanks to employing internal memory for storing the working set
- There are no complex joins
- MongoDB.com supports the database manager.
What Are the Drawbacks of MongoDB?
MongoDB has its share of disadvantages as well, including:
- It doesn’t support transactions. Although fewer applications require transactions today, some still do need it to update multiple collections or documents
- It lacks triggers, something that makes life easier in relational database management systems (RDBMS)
- MongoDB requires more storage than other well-known databases
- It doesn’t automatically clean up its disk space, so it must be done manually or with a restart
- It isn’t easy to join two documents in MongoDB. If you need to pull data from multiple collections using a single query, you’re out of luck
- Finally, you better ensure that your indexes are correctly implemented or in the correct order. Otherwise, MongoDB’s speed drops significantly
If you plan on pursuing a position where you need knowledge of MongoDB, then you need an understanding of its pros and cons. Additionally, brush up on your familiarity with these MongoDB interview questions.
Similarities Between Cassandra and MongoDB
Let’s do some review here and spell out what Cassandra vs. MongoDB have in common.
- They are both open-source
- Both have been around for over ten years, so they’re well-established
- Both are compatible with macOS, Linux, and Windows
- They are both classified as NoSQL databases
- Neither system can replace the traditional RDMS, so if your data needs to be in a structured format using rows and columns, neither of these will do
- Neither system replaces ACID-compliant databases. If your database transactions need ACID, stick with a relational database like PostgreSQL or MySQL
Spelling Out the Differences Between Cassandra vs. MongoDB
Now let’s call out the significant differences between the two database management systems.
- Cassandra uses a traditional model with a table structure, using rows and columns. MongoDB employs an objective-oriented or data-oriented model
- Cassandra offers an assortment of master nodes, while MongoDB uses a single master node. As a result, Cassandra provides higher availability, compared to MongoDB’s limited availability
- While both offer better than average scalability, Cassandra provides higher scalability thanks to the multiple master nodes
- Cassandra has a dedicated in-house query language, CQL, whereas MongoDB’s queries are structured into JSON fragments
- Cassandra has no internal aggregation framework, relying instead on tools such as Apache Spark and Hadoop. MongoDB has its own aggregation framework, though it’s best suited for small to medium-sized data traffic loads
- MongoDB supports ad-hoc queries, aggregation, collections, file storage, indexing, load balancing, replication, and transactions; Cassandra offers core components like clusters, commit logs, data centers, memory tables, and Node
So, Which One Should You Use—Cassandra vs. MongoBD?
It depends on your needs. If you’re in the market for a database management system that offers excellent reliability even during frequent scaling and ease of setup and maintenance, go with Cassandra. It’s especially useful if your business or organization is subject to rapid growth or requires working with transactional data.
But if you require scalability and caching for running real-time analytics, then go with MongoDB— especially if you’re working with content management, mobile apps, real-time analytics, or IoT applications. It’s also ideal for situations where you are working with unstructured data or structured data with no clear definition.
Do You Want a Career in Big Data?
If you’re considering Cassandra vs. MongoDB—or any other database management system—, you might also be interested in a career as a data analyst or engineer. Data is king, and there’s always a demand for professionals who can work with it.
Simplilearn offers a variety of informative courses that will prepare you for an exciting career in many positions related to big data. Check out the MongoDB Certification Training course. The course helps you master data modeling, ingestion, query, sharding, and data replication using MongoDB. You will also learn to install, update, and maintain the MongoDB environment.
But the real standout among big data courses is the Big Data Engineer Master’s program. Created in collaboration with IBM, the course provides online training on the best big data courses, giving you the skills needed for an exciting career in data engineering.
