What makes Cassandra different!!!!
June 07, 2016

What makes Cassandra different!!!!

Anonymous | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User

Overall Satisfaction with Cassandra

I had used Cassandra in my academic projects which were related to cloud computing. I used it for a few projects on Salesforce where multi tenancy features are implemented. In such scenarios Cassandra was one the best choices for NoSql. Although we have used RDMS, the performance while using Cassandra was better.

I have simulated a few real time running apps like Facebook and Uber where I have used RDMS and Cassandra, and checked the performance using Jmeter. It clearly shows that Cassandra boosts the performance over RDMS. One thing I find difficult in Cassandra is following the documents, which are not so understandable.
  • Undoubtedly performance is an important reason
  • We have not encountered a single point of failure
  • Scalability of Cassandra is good which is the most important for the companies where demand is scaling day by day.
  • Cassandra has a wide range of asynchronous jobs and background tasks that are not scheduled by the client, the execution can be eccentric.
  • Because Cassandra is a key-value store, doing things like SUM, MIN, MAX, AVG and other aggregations are incredibly resource intensive if even possible to accomplish.
  • I think querying options for retrieving data is very limited.
  • I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
  • Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.

These are the features which makes Cassandra different from others:

  • Cassandra is a distributed datastore, with a built-in coordinator. This means that requests are intelligently forwarded to the correct node.
  • It is generally very fast, and especially shines with write heavy workflows.
  • It scales linearly. If you double the nodes, you’ll double your throughput.
  • Embraces eventual consistency.
  • Masterless replication across data centers means that your data is always accessible.
I used it while I was doing my academic projects, since the project is over I am no longer using Cassandra currently.
Well Suited
Tunable Consistency
Write Speed

Less Appropriate
Ad-Hoc Queries
Unpredictable Performance

Using Cassandra

175 - We simulated the Facebook Application by continuously adding users .