DataStax Enterprise

Scaling

Speed of data access

Ease of use with those familiar with traditional SQL

Best in class support team

Hybrid on-prem / cloud solution with Astra.

Better compatibility with prior versions in terms of codebase.

Horizontal scalability

High availability

Fast writes

Query flexibility

User experience

Node density

Easily and highly Scalable

Simple UI

High uptime

Cassandra is a bit difficult to learn and understand

The costs are slightly higher for our company

Hardware requirement is moderate to high at the beginning

Scalability: it provides near linear scalability being based on open source Cassandra

Opscenter: it is a powerful and complete tool for monitoring

You can use Spark for analytics workloads

Requires investment on hardware

Initial setup could be cumbersome

You need to be careful to use it only in the right context

Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.

Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.

Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.

Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.

The move from SQL to NoSQL paradigm is always difficult for people who have been using SQL for most part of their technical lives. Even if NoSQL has better performance and is more scalable, the database interface/functionality needs to be seamless for users. This has always been the top challenge. Now with the advent of ACID and horizontally scaling Google Spanner, the competition is rife for what a database can provide.

Though one can be immediately productive, if you get corner cases in your usage with Datastax Cassandra, you have to really know it better. There is a learning curve. Understanding Cassandra server logs, audit logs and sstables helps.

Debugging can be longer especially if you hit corner cases, like not using Light Weight transaction correctly, timestamp ties or getting RuntimeException on scrub/repair/compaction (java.lang.RuntimeException: 30623431613136352d656433372d343939322d393066342d366632313961393530353062 is not defined as a collection) and such.

Datastax Cassandra has great benefits in product, and features but there are costs on infrastructure maintenance and regular operational tasks. Not that there is any technical component that can self heal :-), but this time investment in Datastax Cassandra is more compared to SQL db, say MySQL.

It is always up, very fault tolerant.

Tunable consistency, flexible in that regard.

Nice management tools.

Support for aggregation functions is still limited.