Main Characteristics
- Strong consistency
- Built on top of Hadoop HDFS
- CP on CAP
- Best Optimized for read
- Best for row range based scan
- Strict consistency
- Fast read and write with scalability
- Analytics and Transactional
- Application need full table scan
Cassandra :
Key Characteristics:
- High Availability
- AP on CAP
- No SPF (Single point of failure) – all nodes are the same in Cassandra
- Data is automatically replicated to multiple nodes for fault-tolerance.
- Replication across multiple data centers is supported
- Failed nodes can be replaced with no downtime.
- Cassandra is suitable for applications that can't afford to lose data, even when an entire data center goes down.
- Read and write throughput both increase linearly as new machines are added, with no downtime or interruption to applications.
- Simple setup, maintenance code
- Fast random read/write
- No multiple secondary index needed
- Secondary index
- Relational data
- Transactional operations (Rollback, Commit)
- Dynamic queries/searching on column data
- Low Latency
Key Characteristics :
- Schemas to change as applications evolve (Schema-free)
- Index: Full index support for high performance
- High Availability : Replication and failover
- Auto Sharding for easy Scalability :Sharing data across multiple node for high optimization operation :(Sharding is the process of storing data records across multiple machines and is MongoDB's approach to meeting the demands of data growth :Wiki)
- Rich document based queries for easy readability
- Master-slave model
- CP on CAP
Suitable for :
- Semi structured content
- Replacement of RDBMS for web applications
- Real Time analytics ,High logging and caching
Not Suitable for :
- Highly transactional systems
- System require with foreign key