DataStax Enterprise

Real-time transaction processing (both reads and writes) is where DataStax Enterprise shines. It's very fast with linear scalability should more resources be needed. Additional nodes are added very easily. DataStax Enterprise on its own (without Solr or Spark enabled) isn't well suited for long complicated reports. The data model doesn't support joining multiple tables together which is common in BI reporting.

DataStax Enterprise's NoSQL database (Cassandra) shines where scalability is critical to success. Data write performance is best-of-class. However, be prepared to go through a steep learning curve. The data model and query options are difficult to master. It is not easy to find skilled people to design and support the database. It will take courage and dedication to implement the solution correctly in your organization. The bottom line is that DataStax will not be suitable for all use cases. Make sure you understand the limitations. Start small and grow as you learn. If you use it for the right reasons, it will serve you with excellent results.

DataStax has a good scalable option with multiple clusters and a good write rate. Cassandra also is improving and is an open-source technology that has good community support. The UI is also easy to understand and implement required functions.

The best scenarios where to use it are when you need a really high write rate and you know the queries you are going to execute in advance. If you don't know how you will access the data in advance it is better to look at other solutions.

Datastax Cassandra is a Java based linearly scalable NoSQL database, best-in-class tunable performance, fault tolerant, distributed, masterless, time series database and has easy-to-use administration and monitoring functionality with opscenter. Configured correctly there is no downtime and no data loss. The documentation is exhaustive, and the community is agile and supportive, and Datastax provides good support. For all these reasons, Datastax Cassandra has become a NoSQL technology of choice for many platforms.

However it has some time investment on infrastructure and regular operational tasks, and if you do not have bandwidth for it, a managed NoSQL solution like DynamoDB might be more appropriate. Also if you have search needs on Cassandra and do not have corresponding Spark/Solr setup, Datastax Cassandra might not be ideal for you.

DataStax is best for simple data schema with high speed of writes. Data layout and modeling is centered around how it is going to be queried. It's not very appropriate for complex ad-hoc querying and analytics.