We developed a Product Information Management system tailored for e-commerce. This homegrown system has evolved into a Software-as-a-Service offering available on the marketplace. The primary challenge addressed by this solution was managing vast amounts of data associated with products.

In this context, major e-commerce players like Amazon handle billions of images, regularly updating metadata and product attributes. The details visible on platforms such as Amazon, Alibaba, or Walmart, encompassing product specifications like laptop configurations, processors, RAM, etc., involve handling an enormous volume of information. 

For this use case, a key requirement was a reliable system with high uptime that did not adhere to the traditional master-slave or leader-follower architecture. Initially opting for Cassandra to meet these criteria, we encountered challenges related to the availability of skilled developers and Database Administrators. Consequently, we decided to transition to MongoDB to address these technical skill constraints.

We used the product because we wanted a database to handle heavy write workloads. Our events had time series data, so we found the product useful.

This solution was a component of our messaging system. We used it as a high-capacity memory-based database.

We use the solution for database management.

We set up our own Cassandra cluster. Cassandra is used in our processes.

It's running in the cloud. As previously stated, we use Azure for virtual instances and we set up our own cloud server there.

Cassandra is used for most of our applications that don't require a lot of associated data, such as video and a model.

Cassandra can be deployed on-premise and in the cloud.

We are storing all our analytics application data in Cassandra.

Our primary use case of this solution was for working on PNRs and user journey plans for an airline. Things such as check-in times, airport arrival time, boarding times, etc. We stored all that data in Cassandra. I currently work as a chief technology officer.

We use Cassandra for our applications.

We are using this solution for IoT projects where there is a need for high-performance runtime databases.

We deploy this solution on-prem and on the cloud. I'm a senior data architect manager.

I was working for a client where there was a huge amount of data, where all the networks were intercepted. We used to do analytics on top of it. We did entity profiling. We take data and we use it to build profiles for users. Then we profile how many emails the user is sending. We see his complete profile and his behavioral traits, like what websites he's visiting and his e-commerce activity.

Our primary use case for the solution is testing.

I designed a product catalog data model in Cassandra according to their features and properties, loading millions of data and performing the required queries over it. 

Now, I am getting much better performance than relational databases.

We've used Cassandra in the past to design a right-node read-less ideology. We mainly use it for its database capabilities.

Our primary use case is developing software for others and it's really a solution for enterprise size companies. We're like integrators and we have numerous technical partners that implement. We have a partnership with the company, implementing the service on projects. I'm a managing director of the company.