MongoDB vs Casandra

1. Overview

When it comes to NoSQL databases, MongoDB and Cassandra may seem similar but are quite different. Both have similar use cases but are not intended for transactional data (i.e., accounting systems)

2. Description

2.1 Comparison of Features

Feature	MongoDB	Cassandra
Development language	C++	Java
Storage Type	BSON files(Document-based)	Column(Wide-columns)
Expressive object model	Yes	No
Protocol	TCP/IP	TCP/IP
Secondary Indexes	Yes	No
Transactions	No or Yes(Support for multi-document ACID transactions was added to MongoDB with the General Availability of the 4.0 release)	Local
Performance	Provides faster query execution performance due to simple schema	Provide high scalable and linear performance
Fault tolerance	Master-slave model + failover, with no single point of failure	High availability without a single point of failure
No downtime on node failure	No	Yes
Scalability	Writing scalability is limited in MongoDB	High scalability
Speed	Not faster compared to Cassandra in terms of read operations	Faster for queries of smaller scripts
Query Speed	Reduces network speed while multi-query execution	Multi-Query execution capacity
Read/Write capabilities	Meets low latency requirements for reading requests, at low throughput	Meets low latency requirement for write requests, at low throughput. Not engineered for reading performance
High write throughput	No	Yes
Sharding	Sharding is built-in. But vs Cassandra, MongoDB shards are replications of multiple servers	Auto-sharding, with a different effect on its replication. In Cassandra, each shard is a server, with its data replicated across other servers
Querying	"Query by example" model. Mongo can execute complex, dynamic queries. but it's not necessarily the best fit for reporting-style workloads or complex transactions	Predictable query performance, but being a key/value store it can be a bit more tricky than MongoDB. it allows querying by key or key range
Concurrency	Instant update	MVCC
Locks	Yes	Yes
Triggers	No	Yes
Replication	Master-Slave. MongoDB's replication facility, called replica set, provides automatic failover and data redundancy. Replication needs to be set up, but Mongo has clear guidelines to help	Multi-Master. Replication with Cassandra is very simple. It mostly takes care of it all for you. Just indicate how many nodes you want your data copied to and it automatically handles the rest.
CAP theorem	Consistency, Partition tolerance	Partition tolerance, High Availability
Operating System	Linux, Mac OS, Windows	Linux, Mac OS, Windows
Data storage	Disc	Disc
Characteristics	Retains some SQL properties such as query and index	A cross between BigTable and Dynamo. High availability
Hadoop support	MongoDB Connector for Hadoop	Native Hadoop support, including Hive and Pig
Data Integration	Fast and Flexible with different applications and tools such as Big Data	Fast and Flexible with different tools
Pricing	Open source and depends on the implementation and has different licensed versions too	Open source and depends on the implementation
Syntax	Requires you learn a new query language	CQL is easier to learn alike SQL than MongoDB
Areas of use	CMS system, comment storage	Banking, finance, logging

 

3. References

https://www.semanticscholar.org/paper/NoSQL-databases%3A-MongoDB-vs-cassandra-Abramova-Bernardino/a6d3ceea74deba7ba762ec051492d79794933e98/figure/1

https://www.upwork.com/hiring/development/mongodb-vs-cassandra/

https://scalegrid.io/blog/cassandra-vs-mongodb/

https://www.educba.com/mongodb-vs-cassandra/