The use of Cassandra in real-time data analytics has been pivotal for our e-commerce platform. As our platform operates 24/7, providing services to sellers and customers alike, the need for real-time updates is paramount.

For instance, when a customer leaves comments or feedback on an image, they anticipate an immediate reflection of these changes on the portal. Similarly, sellers altering product attributes or updating images expect instant visibility of these modifications.

Handling large data volumes with Cassandra has been an excellent experience. Despite challenges related to the influx, these were not attributed to Cassandra itself but rather to middle-layer issues. Generally, it demonstrated scalability with workloads, thanks to its horizontal scaling capabilities. We could easily add new nodes to the system as needed, ensuring the platform coped well with increasing loads.

The tool's most beneficial feature for scalability is its entire architecture. The absence of a single point of failure or a leader within the ecosystem contributes to its robust scalability. This key aspect influenced our decision to opt for the Cassandra ecosystem.

In terms of performance, it demonstrated the ability to handle approximately 1.6 billion requests per day. This was achieved on AWS using EC2 instances, and it was during a period about four to five years ago.

Cassandra is available most of the time. It is quite good for what it is made for. We write tons of time series data for the DB. We can add almost one million columns to the solution. It is awesome.

The most valuable features of this solution are its speed and distributed nature. 

The most valuable feature of Cassandra is its fast retrieval. Additionally, the solution can handle large amounts of data. It is the quickest application we use.

I am satisfied with the performance. So far it has done fairly well. There haven't been any complaints.

The most valuable features of Cassandra are the NoSQL database, high performance, and zero-copy streaming.

I think the time series data was one of the best features along with auto publishing. For logging purposes, for example, you can say that after 30 days you won't need the data anymore and it goes. It was a great fit for our requirements. The good thing is that every cluster, every node in the cluster synchronizes the data in real time. That is something amazing that we loved.

Cassandra is good. It's better than CouchDB, and we are using it in parallel with CouchDB. Cassandra looks better and is more user-friendly.

Some of the valued features of this solution are it has good performance and failover.

Cassandra has some features that are more useful for specific use cases where you have time series where you have huge amounts of writes. That should be quick, but not specifically the reads. We needed to have quicker reads and writes and this is why we are using Cassandra right now.

The most valuable features are the counter features and the NoSQL schema.

It also has good scalability. You can scale Cassandra to any infinite level.

If you need availability and consistency, you can go with Cassandra. 

• Log-structured storage
• CQL (Cassandra Structure Language)
• Ease of installation
• The node setup

Here are some features which have been really helpful in my organisation:

• High Avaialability
• No downtime
• Better performance
• Greater scalability.

HA is one of the great features of Cassandra with no downtime, e.g., you can achieve continuous data without a single downtime because of node to node ring architecture.

Right now, the solution is working very well.

Cassandra has a very good understanding of GBL, and how to cure GBL in time. The biggest problem is always with GBL in terms of understanding the drives' collector and making them work perfectly. Cassandra addresses this very well.

The solution's database capabilities are very good.

I really appreciate the high availability, automated replication, linear scalability, and automated region fail-over.

• Simple ring architecture
• Replication using peer-to-peer protocol rather than leader selection
• Linear scalability (99%)
• Configurable consistency

The most valuable feature for us is the technical evaluation, it's the best technology. Cassandra is good for us.