Cassandra Reviews

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.

The solution provided us with more than 100K PNRs a second and because the company was international there was a heavy data write, and at the same time a heavy data read. Cassandra helped us a lot, specifically to heavy write the data which was helpful and an amazing solution for us. 

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.

One of the issues with the solution is that you cannot drop write like you're able to in MongoDB and MySQL, where you can join tables. Cassandra doesn't have joins between tables so you need other tools for that. You need to read all the data and put in memory and then add the joins. That is the area where I think they need improvement. Secondly, for example, when setting up your cursor, you have to be very sure about the read mechanism, because if you're not following the read mechanism and mistakenly build a key that is no longer unique then you start overriding data. There are a lot of improvements they could make including on the OS.

The stability is good although sometimes the solution slows down. I liked it and it's good for big data. 

The solution is scalable. If you need more nodes in your cluster, you can simply turn on a new node and it will automatically start synchronizing data. In real time, it will start sinking the data with that node. And that is a boost, that's the best one. The entire company was using the solution. 

Because we used a vendor, they supported us on technical issues and were very good. I do think they needed to improve their documentation. 

I have also previously used MongoDB which, from a technology perspective, has a collection base while Cassandra keeps data in the tables. It's a major difference. Every platform has its pros and cons. Cassandra does not provide an adopter kind of scenario. You need to use third parties to manage the relations. These are the differences and similarities but Cassandra does have a table structure which MongoDB does not have.

The vendor helped us with implementation. We had a team of around 25 working on deployment. Deployment was in multiple regions so it would definitely take a few hours, but let's say a three node cluster can be implemented in a couple of hours. It's a matter of understanding the architectural aspects. Once you have that you can decide on configuration.  

This was for an enterprise company and they are expensive. Cassandra has a heavy pricing mechanism because it's a yearly license. I'm pretty sure we were paying something around $50,000 annually at that time. 

I would suggest not over-complicating things. If you really need to have heavy write and you are okay with building keys by yourself, then go with Cassandra. If not, then the culture base is there, MongoDB is there. And MongoDB is the best one. If you are not enterprise, then don't kill yourself. Once I started working on Cassandra, the biggest lesson for me was needing to build. I need keys to retrieve data. If my key and the primary key is not well settled or well configured, then it is very tough for me to read data. 

I would rate this solution a seven out of 10. 

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.

My client was looking into customer profiles and then doing analytics. I captured the data part and designed the schema. They would do an analysis from that data and would find out potential customers who would buy their product. They would find these things out and then project their marketing and sales to those customers.

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.

For my use case, it was more than sufficient. I used most of the features, whatever was available. I'm not sure what else can be improved.

We had very new data of almost 10 million people and it was very fast. We also found the scalability and performance side to be very good. It is stable and available. 

During the time it was not stabilized, there were maintenance requirements, but once it was stabilized, we did not have maintenance. Three people are required for maintenance. 

We use it very extensively. Almost a hundred people are using it.

We don't have any complaints about technical support. 

I have worked on GraphQL, MongoDB, and ActiveDays.

You cannot compare a MongoDB with Cassandra. They are very different because MongoDB is more document-oriented and Cassandra is a columnar database. You can compare it to Couchbase but comparing Couchbase to Cassandra is easy because Couchbase requires a lot of infrastructure to deploy and install it. 

We worked on complex scenarios, so the setup was complex. The Cassandra deployments were fine. The cluster and the profiling of the cluster did not take much time. We had some processes in place. It takes around half an hour to an hour. Fine-tuning was a bit of a challenge. 

It's a good tool and it's a growing tool. The support is good. I would definitely recommend it.

I would rate Cassandra a nine out of ten. Nothing is perfect but I believe that continuous improvements are coming.

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.

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

There could be more integration, and it could be more user-friendly.

I have been using Cassandra for one year.

We are not using the most recent version, but rather the one prior to the most recent. Not the latest version.

Cassandra is a stable solution.

Cassandra is a scalable solution.

We have 32 projects running on Cassandra.

We have plans to increase our usage.

I have not contacted technical support.

I have since left the university. I am currently working in the Czech Republic. 

My role has evolved significantly, and I am now more involved with OpenShift. It's also very self-contained.

We use OpenShift on Microsoft Azure in the Google Cloud.

For storage, we are using NetApp Trident ONTAP. It's an ONTAP Network Access Storage.

We work mostly on Cloud solutions. We're getting reserved instances from Microsoft Azure in Google Cloud. 

All our storage is running on NetApp Trident ONTAP.

They were previously using MongoDB, and I'm not sure why they switched to Cassandra.

The initial setup is not at all complex.

I'm not sure how long it took to deploy, but I believe it was about two weeks from the design to live production.

We have a team of six technical guys working on deployment and maintenance.

We were able to complete the installation in-house.

There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly. That is handled by the commercial department.

I would definitely recommend this solution to those who are considering using it.

I would rate Cassandra a nine out of ten.

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

We are storing all our analytics application data in Cassandra.

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

Cassandra can improve by adding more built-in tools. For example, if you want to do some maintenance activities in the cluster, we have to depend on third-party tools. Having these tools build-in would be e benefit.

I have been using Cassandra for approximately four years.

We have experienced zero downtime using Cassandra. It is highly stable.

Cassandra allows us to scale the cluster when we have increased loads on the fly which is useful. The scaling can be done easily and quickly, within a few seconds.

We have approximately 40 people using the solution as part of our applications team.

We have more applications coming and we are onboarding different applications with Cassandra. We plan to increase usage.

We used other solutions previously, but we had to switch to Cassandra because we had limitations we could not overcome. Cassandra is a NoSQL database and it's a highly distributed and scalable database and this is why we choose Cassandra.

Cassandra's installation is straightforward. The documentation and very good. We have a lot of automation scripts in place. We were able to implement the solution within a minute, we were able to build the class in the cluster with the right automation in place.  

We do the deployments ourselves. 

We are using the open-source version of Cassandra, the solution is free.

I would recommend this solution to others. Cassandra is a highly scalable NoSQL database system where if you have a lot of data, for example, in the millions in volumes of data you can.

I rate Cassandra an eight out of ten.

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

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

The solution is not easy to use because it is a big database and you have to learn the interface. This is the case though in most of these solutions.

I have been using the solution for approximately one and a half years.

The stability of this solution has been good in my experience.

I have used Druid, Neo4j, and MongoDB previously.

The installation was not difficult. I have my DevOps team of six engineers that does the installation, maintenance, and everything else related to the solution.

We do the implementation of the solution.

I have also evaluated MongoDB and the performance of this solution is better. Additionally, I prefer this solution to MongoDB because when there is a lot of writing happening, MongoDB is better at reading. It is stable and a fantastic solution, but it does not mean that it fits everywhere.

When it comes to the ease of use of a solution it is not what matters, I do not look at it from this perspective. I am mostly concerned with the performance because as a developer and expert, we do not look at that easy of use we just want it to perform well. Even if it is a little bit complex, it is okay. The performance is the only thing I care about because if you are tech-savvy you should be good enough to write a code and use the function.

I would recommend this solution to others.

I rate Cassandra an eight out of ten.

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 secondary index in Cassandra was a bit problematic and could be improved.

Cassandra can improve by having an ecosystem integrator that was more complete. For example, in some maintenance operations, we needed to deploy external tools to perform tasks that were not packaged alongside Cassandra.

I used Cassandra within the last 12 months.

Cassandra is a stable solution.

I have found Cassandra to be scalable.

I would recommend Cassandra for larger enterprises. It's not as useful for small or medium enterprises.

I have used other solutions similar to Cassandra, such as Couchbase.

The main differences between Cassandra and Couchbase are, Couchbase is more for general purposes, and it has a smaller latency. Whereas Cassandra is easier to manage with the open-source version in clusters environments.

The initial setup of Cassandra was simple. There is a large community that offered a lot of support.

We did not use professional support because it was not necessary. We found all the information we needed from the documentation.

Cassandra is a free open source solution, but there is a commercial version available called DataStax Enterprise.

If you want technical support, you will need to pay for it.

I rate Cassandra a nine out of ten.

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

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

If you have a requirement of aggregation and joints, Cassandra doesn't support a solution that can give the aggregation. If they were to include these two areas, the aggregation and the complex joints, it would improve the solution a great deal. 

The solution is scalable. 

We now have a lot of regulatory compliance in the Middle East and they try to keep things local, including customer support. Most companies use the community version and not the enterprise solution.

The initial setup is generally straightforward and not overly complex. You can also look on Google and various YouTube clips for information on the setup. 

In the UAE or in the Gulf region, you're required to buy from a local vendor so prices will vary from vendor to vendor and region to region. We have a monthly license and you can generally bargain for a better price.

It's important to have a data architect or consultant on hand who knows the technology and can judge whether it's a suitable product for the use case. 

I rate this solution eight out of 10. 

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

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.

We actually find HBase to be faster and better than Cassandra.

The disc space is lacking. You need to free it up as you are working.

I have about ten years of experience working with the solution.

We have some experience with HBase, which we find to be a faster solution.

My first Cassandra project was with a project introduced to us by Facebook. That was ten years ago. There was a time I tried using it a couple of months ago, and I completed the project for Upwork for Cassandra. Right now, I have another project which is using a Cassandra cluster which is under my management. Previously, I had quite a big Cassandra cluster of about 100 nodes and about 500 terabytes of data.

Overall, I would rate the solution nine out of ten.