Cassandra Reviews

My use case for Cassandra is for a document and other unstructured data management system as well as structured data for ultra-poor member community edition, community members' PII information, so that's a secure database. I understand that, and MongoDB is another environment we have already introduced. I have already informed you since two years ago that it was utilized in our HMPP health data, healthcare data, so there is no issue in that environment. Basically, we are using it in our GCP environment, all environments are on GCP.

The functions or features in Cassandra that I have found most valuable are that it is a distributed system similar to Mongo. It's good enough for comparison with another SQL database, so it's smooth and organized for distributed database system.

The peer-to-peer architecture in Cassandra is helpful for network decentralization, and I have already introduced that feature. Cassandra features in peer-to-peer as well as another monitoring, so basically, it's good enough for our service.

The tunable consistency level in Cassandra is good, and we are using that feature already. In terms of built-in caching and lightweight transactions in Cassandra, the transaction level is good, and it's optimized, so there are no more issues in that database.

Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there. Additionally, the database monitoring system or auditing system is well-comparable with other database systems, so we are actually happy to be using this Cassandra database.

Regarding areas of improvement for Cassandra, currently, we are not facing significant issues. Some issues arise from our vendors like Apache slowness and distribution or load balancing from HAProxy, which should better handle consumption for high-level concurrency.

I think it would be great to have a better open plugin library, where any kind of Apache could be included in Cassandra database, as well as a built-in Apache library, which would be better for Cassandra optimization or publication.

I have been working with Cassandra for more than seven years.

I would rate the stability of Cassandra as eight out of ten.

For scalability, my rating for the ability to scale and expand is nine out of ten.

My mark for Apache technical support is seven out of ten.

They should improve response time or quality, which would rate as eight out of ten.

Technical support from the vendor is more than enough, and they are knowledgeable, so I think there is no problem from the vendor side.

Positive

The setup process for Cassandra is easy and not complex, not plenty for technical people. As a technical person, I have no issues with it.

The pricing for Cassandra is a little bit high, so it would be better for our community services if they consider community pricing for any non-profit organization like an NGO or other things. It would be better to have enterprise-level features in our community edition, which could support our future development for global community development.

We already used MongoDB and upgraded the version to the latest version on that, and also, we are using Cassandra and another OLTP database like PostgreSQL, MS SQL, SQL Server, and MySQL. Our ERP database is EDB, PostgreSQL database.

We are using a peer-to-peer cluster in Cassandra.

My assessment of multi-data center replication and disaster recovery for Cassandra is that recovery is currently not introduced in our environment, but we hope it would be included in our auto recovery module. Currently, we are recovering the whole VM snapshot in our GCP environment, and that's why we are not taking care of that backup and recovery process. We focus just on the backup process in GCP VM which is snapshot, and it happens every night. It has already happened in the GCP bucket environment as well as in another region, so we're not looking directly for any recovery system. I hope it would be introduced hopefully next year or the following year for the recovery process because we are already introducing it as part of our policy for database backup and recovery process as a DR system. Once that policy is published, we will introduce our recovery system or DR system for every database environment.

Though we are not extensively using Cassandra CQL, some of us are using that one, but we are using a common tool like DBeaver or HeidiSQL. In most cases, we are utilizing that open source or community edition because we are a non-profit organization, so that's why we consider that.

Cassandra is deployed on VM, and that VM is built on our GCP environment, Google Cloud environment.

My comparison of Cassandra with products from other vendors indicates that competitors are basically organizations like BRAC, along with others such as BN and INGO and ASA International, who are using the Cassandra application. I think most of the people are aware that Cassandra is a good distributed database system for transactional use, and it tends to perform better with clustering or replicated database distribution. Most people appreciate that database, so I think it would be better in our Bangladesh market.

I rate this review overall at eight out of ten.

We have some big logs, and we need to do some AI analysis. Currently, we are storing data on Cassandra, and we are checking which database has fast retrieval. We have done a couple of load tests and have found good results with Cassandra, so we are using it.

Its retrieval is similar to an RDBMS, so our team finds it easy to adapt. Our team is involved with the database mainly for retrieving data. We found a good capability in Cassandra, and we found this read replication somewhat easy compared to other options. For this reason, we want to use managed services. To forecast costs, we created our own PR custom launching to avoid some cloud costs.

We found some issues with the batch inserts when the data volume is large. Batch insertion is needed when I want to insert a million records at a time. We have some settings for batch inserting compared to other databases. Batching bulk data can cause performance issues.

I have been using Cassandra for the last three years. I have been using Neo4j for the last eight years, but my total experience with Cassandra is around three years.

There are around six issues. Only the bulk intercepts are nice compared to MongoDB. Postgres is somewhat similar.

Technical support is found through the online community. We have used the same resources, however, we found the right support compared to others.

Neutral

Right now, we have implemented Cassandra and Neo4j. With some load testing, we found that Cassandra is easy for our team to adopt.

Comparing to MongoDB, for retrieval, Cassandra is okay. That said, we need to write some complex queries like aggregations. We have faced a few problems with MongoDB in comparison, like aggregations and other things, which we found easy with Cassandra.

I did not find any difficulties. Basically, we have done a POC for around one month. After that, it takes one day the next time.

I am the developer and one of the financial contributors. I am also the technical architect. Before choosing a database, we need to choose what is available as per our requirement. I am not aware of the financials.

For us, the key component on the developer side is that it's very easy. We are doing so instead of managing servers, we have used our on-premise installations. The cost for us is negligible.

Application users might be +5,000, however, developers start around eight to ten. Right now, this project is stable. We will start new projects where we will implement improvements.  

I recommend it. It should have good standing in the market right now. 

I am the VP of technology. 

I'd rate the solution ten out of ten. 

Neutral

We use Cassandra mainly for key certificate and key management. Additionally, we use it for handling large-scale data management, particularly in the telecommunication nature of our applications.

Cassandra handles large-scale data management adequately without major issues, even during peak times. Its scalability fulfills our basic requirement for managing large data volumes.

The most valuable features of Cassandra are its scaling capabilities and its non-SQL nature capabilities.

We experience configuration issues when accommodating the volumes we require, which often necessitates consultation with the Cassandra development team. This aspect is room for improvement. 

Additionally, the initial setup was complicated and required a lot of back-and-forth questioning. The documentation could be improved to better reflect exceptional use cases.

I have been working with Cassandra for a couple of years.

Cassandra is stable in handling large data volumes, although we encounter occasional trouble report bugs due to configuration.

Cassandra's scalability is rated as seven out of ten, fulfilling the requirement for our data management needs, though there might be room for improvement.

The external technical support for Cassandra provides a pretty good response, though the response time is not as immediate as we would like.

Positive

Cassandra is part of a new product, so we did not use any different solution for these use cases before.

The initial setup was challenging, involving extensive configuration and consultations with the development team. The documentation did not clearly address exceptional use cases.

I am not familiar with the experience of pricing, setup cost, and licensing.

We evaluated other solutions before choosing Cassandra, focusing on its non-SQL nature and scaling capabilities. However, I do not recall the specific vendors considered.

I'd rate the solution eight out of ten.

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.

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.

There were challenges with the query language and the development interface. The query language, in particular, could be improved for better optimization. These challenges were encountered while using the Java SDK. 

I have been using the product for six months to a year. 

Cassandra is considered a stable product, and stability issues were not encountered on the product side during deployment. The challenges were more related to the SDK and development aspects, particularly in implementing complex logic.

The tool's scalability is excellent, with the ability to easily add nodes to handle increased workloads. On a scale of one to ten, it is rated around eight. I worked with a single customer on Cassandra, as it was a specific experience. However, as a service provider, we handled about two dozen B2B customers on the e-commerce side.

The tool's setup is considered to be of medium complexity on a scale of high, medium, and low.

The tool's benefits include its horizontal scalability, making it well-equipped to handle a massive influx of data and billions of requests.

We used the tool's open-source version. 

I rate the product a six out of ten. I recommend conducting a simple proof of concept to test and validate Cassandra for specific use cases. Start with a small chunk of your actual use case, and then proceed accordingly. It's crucial not to overlook the logic part during implementation, as this can have a significant impact on the overall success of the deployment.

We use the tool to get unstructured data into a database so I can do data analytics. It's all internal; we do not sell it outside of the company. 

I gobble up all the information that is available to me. I grab emails sent to us, PDF files, and Word files and read the contents. I try to get labeling for those unstructured data and do analytics on it with Python.

Since I haven't had years of experience with it, it's still new to me. One valuable feature is its distribution, so I can run it partly in the cloud and part on-prem. That's a feature I'd like to use but haven't yet because we're trying to move to Azure. I don't know if or when that will happen. Ideally, we'd have it distributed over the cloud and on-prem simultaneously, so if something happens to our on-prem, we can keep going in the cloud, like a pay-as-you-go model with Azure.

I want Cassandra to update its open-source version more quickly. It's already feature-rich, but I'd appreciate better integration with other NoSQL databases like MariaDB or MongoDB. If I ever need to work with customers or vendors using different NoSQL databases, having native integration in Cassandra would make managing and interacting with their databases much easier.

I have been using the product for more than a year. 

I haven't contacted support yet. I would appreciate the community support being more accessible. It would be beneficial if the maintainers provided more information, such as detailed use cases. For example, instructions on using Cassandra to analyze data for a business or a streaming service would be helpful.

The tool's deployment is straightforward. Right now, I'm focusing on creating a proof of concept for my bosses to demonstrate Cassandra's capabilities and how it can help our organization grow and become more efficient. 

I use the tool's open-source version. 

If the proof of concept goes through, we might use it for data analytics and KPIs. We could also use it to store our EDI for our customers instead of using a value-added network for EDI transactions. We could handle all that in-house.

You could use Cassandra to scale by setting up a tiny copy on the internal network. My vision for it is that instead of paying a third party for EDI transactions, we could handle everything in-house. This way, both we and our customers benefit. If it turns out to be cheaper, that's great. If it's more expensive, I can inform my boss, and we can decide whether to continue.

I rate the tool's ease of integration with existing infrastructure a six out of ten. 

I rate the overall product an eight out of ten. 

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.

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 product is a NoSQL database. While working with it, we have to structure the table the way we want the query. We cannot get data from another table because, in Cassandra, we do not have any joins. Depending upon our schema, we can't make ORDER BY or GROUP BY clauses in the product. 

We should know the data we want before making the table. Only after that we can create the table. Or else we will face issues with our server, and we will have to fetch all the data and compute it in the programming language. It will become messy. It is the main drawback of the solution.

I have been using the solution for six months.

For a provided environment, it is stable most of the time. The stability depends upon the query or timeout we configure when setting up the DB. I rate the stability an eight out of ten.

The solution is scalable. If we want a database that has a high write speed, it is awesome. I rate the scalability a nine out of ten.

The initial setup is quite easy. We can install it on our VMware. It is quite straightforward. I rate the ease of setup an eight out of ten. We host the solution in VMware on Azure and install it.

I am using the latest version of the solution. PostgreSQL has limitations while adding columns. Cassandra is a self-managed service. If someone wants a solution with a heavy write speed of time series data and knows the queries they need to make before creating the table, they should invest in the product. Overall, I rate the solution an eight out of ten.

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

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

It can be difficult to analyze what's going on inside of the database relative to other databases. It can also be difficult to troubleshoot sometimes.

We found this solution to be very stable. 

This solution was very scalable. We had 5,000 transactions a second, and approximately one third of those are unique users at any one time.

We had a small maintenance team for Cassandra. It was just supported by the development team.

I don't have the specific numbers on pricing, but it was fairly priced. 

Because it's such a unique database system, I would counsel people to use it only in situations where it solves a specific problem. You can't just replace it like you can with SQL Server and Postgres, which are kind of corollaries. Cassandra's a bit of a unique animal. It solves specific problems, and you should choose it when you need to solve problems that it fits.

I would rate this solution as an eight out of ten.

We use the solution for database management.

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 have been using Cassandra for approximately six months.

The solution is stable and secure.

The scalability of Cassandra is good. You need to start with UNIX and then you can utilize your data store. It's very easy to scalable.

We work in teams and the solution can be used for 100 to 1000 people. We have plans to increase our usage.

I have not used the support from Cassandra.

We use other database solutions prior to Cassandra. When we run into issues we use the internet and search for solutions.

The initial setup of Cassandra can be difficult in the configuration. There might be a need to have assistance. The implementation process can six months for connecting to certain databases.

We use fix people for the maintenance of the solution. The team consists of engineers and developers.

I rate Cassandra an eight out of ten.