Having a robust functional database is essential for the optimum performance of your enterprise applications. At this time, many of the enterprise users are looking for a reliable NoSQL database as these can serve to the needs of scalability and performance at best. Suppose you are also on the lookout for a robust NoSQL database. In that case, you may have already come across many available options, among which two prominent names would surely be Cassandra and Mongo DB. Both of these have many advantages for each, and they have some disadvantages too, considering various requirements users have. In this small micro tutorial, we discuss these two popular NoSQL database choices, which may help you make better decision making.
Similarities between Cassandra and MongoDB
While comparing Cassandra and MongoDB, you may find some shared similarities among these. Even though those exist, there is not much in common between these two databases. Let us explore these limited similarities first.
Both are NoSQL
Most noticeably, both Cassandra and MongoDB come under the category of new-generation NoSQL databases. NoSQL or not only SQL is a trendy modern alternative of the traditional relational databases. Unlike the SQL database suite, NoSQL may store a larger amount of data without the need for a logical schema or category.
The traditional databases or the SQL DBs are not able to handle a big volume of unstructured data. Still, NoSQL databases can effectively take up this challenge with horizontal scaling abilities. Cassandra was first released back in 2008 and one of the first-generation NoSQL DBs. MongoDB, however, joined the NoSQL database bandwagon a year later to Cassandra.
Another similarity between Cassandra and MongoDB is that both are open source and free license software. You can quickly and freely download these database packages and configure the same with no add-on cost.
The Facebook developers first created Cassandra and now maintained as a freeware Apache project, being a part of the open-source community. However, MongoDB is a very popular DBMS system that is maintained by a robust MongoDB developer community.
Inability to replace RDBMS and ACID
One thing to consider while choosing either Cassandra or MongoDB is that both of these cannot fully replace the traditional RDBMS. If your data storage needs demand rows and columns structured database format, it is most useful to stick to any available powerful relational databases. Also, if you need to have ACIDcompliancefor your database, Cassandra or MongoDB again may not be an apt choice. Most of the NoSQL DBs are probably out of the question with the need for ACID compliance. For transactions that need to ensure atomicity, consistency, isolation, and durability, it is advisable to stick to the relational databases like MySQL, MS SQL, or PostgreSQL. For more insight into making an appropriate choice, feel free to connect with RemoteDBA consultants.
Differences between Cassandra vs. MongoDB
As we have to explore the top similarities between Cassandra and MongoDB in enterprise database administration, next, let us examine the significant differences between these.
- Data availability
One notable difference between Cassandra and MongoDB is in their unique strategies related to data availability. This feature mostly depends on the numbers of the master-slaves in the given cluster. MongoDB usually maintains a single master that reins many slave nodes. If the master node is down, instead of it, one slave node can take over a master’s role. Even though this automatic failover strategy may ensure recovery, this may take up some time for the slave to start acting as the master. There is a chance of the database being unresponsive during this time.
On the other hand, Cassandra is using another unique model, which seems to be better. Instead of maintaining a single master node at a time, it has multiple masters maintained simultaneously in a given cluster. As there are numerous master nodes, the risk of downtime in case even if one fails, is eradicated. This redundant model can also ensure the high availability of data at all times.
So, if your database needs high availability as the essential requirement and depends more on the instant request responses, then Cassandra is ideal to choose. On the other hand, if a 30-40 seconds delay isn’t grave to affect your business badly, there is no need to go for Cassandra for its high availability. Instead, it can avoid the burden of additional infrastructure sticking to MongoDB.
Scalability is another crucial feature and primary need for growing enterprises. This feature has a direct link to the cluster model. MongoDB and Cassandra feature some significant differences in terms of writing scalabilities.
It is a known fact that in the master-slave setup, the only master node may be able to accept input and write. Meantime, the slave nodes may only be used for the reads. So, with a single master node, MongoDB is limited in terms of its write related scalability. With multiple master nodes, Cassandras have increased writing capabilities. It will let the database to coordinate many writes simultaneously, which all come from the masters.
The more number of master nodes out there in the given cluster, the better the writing speed, i.e., scalability. So, if you are considering the writing speed and scalability as a priority, then it is better to consider choosing Cassandra.
- Data model
On examining the data mode of both of these NoSQL DBs, we can find that the data model of MongoDB is categorized as document and object-oriented. So, it can best represent any object structures that are nested for multiple levels. Cassandra, on the other hand, follow a more traditional data model. It has a table structure that uses conventional rows and columns. However, it is mostly flexible compared to relational databases, as each row may not be required for the same columns. On creation, these columns will be assigned to any of the given Cassandra data types. So, if you are looking for rich data models, then MongoDB is an ideal choice as the unstructured architecture of this DB will give you more flexibility.
While making a further comparison, you can also include assessing the query language for both differences in queries, programming language supported, etc. to take an aggregative decision on choosing among these DBs.
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