DataStax Enterprise Reviews

DataStax Enterprise serves as the primary database for all transactional processing in my organization. DataStax Enterprise provides linear scale as well as multi-data center real-time replication of data such that we can maintain uptime even with the loss of multiple data centers. Keeping the system up and the data fresh is of paramount importance for our clients. Performance is also top of mind, and DataStax Enterprise delivers best-in-class performance.

A specific example of how I use DataStax Enterprise in my organization is that there is a learning curve and tasks that are simple in traditional RDBMS systems can be complicated with DataStax Enterprise. However, once I get the hang of denormalizing data and getting the data model correct, DataStax Enterprise is very usable. Usability from a developer's standpoint is very simple, but the complication is on the architectural side with the data model.

I also love the ability to have our self-services up and running even with a total outage at one of our data centers.

The best features DataStax Enterprise offers include scaling, speed of data access, and ease of use for those familiar with traditional SQL.

The scaling and speed of data access have benefited my team because the scaling and the speeding of data provide linear scale as well as multi-data centers' real-time replication of data such that we can maintain uptime even with the loss of multiple data centers. It enables us to maintain our uptime, which is very crucial for our clients.

DataStax Enterprise has positively impacted my organization by providing the ability to have our services up and running even with a total outage at one of our data centers. There is no need to maintain windows since we can turn off data centers while doing maintenance and then put them back in the rotation and move on.

I can share specific outcomes or metrics that show this positive impact, such as improvements in performance of about 60% and a reduction in downtime of about 40 to 45%, which is very great.

I think DataStax Enterprise can be improved by having a hybrid on-prem and cloud solution with Astra. Better compatibility with prior versions in terms of codebases should also be improved.

More ways to reach out to customer support would be great as additional feedback on the needed improvements.

Better compatibility with prior versions in terms of codebase would be appreciated as another improvement needed for DataStax Enterprise.

I have been using DataStax Enterprise for three to four years.

DataStax Enterprise is very stable.

DataStax Enterprise's scalability is very fast with linear scalability and hence is very scalable.

The support team is best-in-class, navigable and easy-to-customize in UI. The customer support is responsive and proactive, but they should find more ways to be reached.

My advice to others looking into using DataStax Enterprise is that real-time transaction processing, both reads and writes, is where DataStax Enterprise shines the most. It's very fast with linear scalability. Should more resources be needed, additionally, nodes are added very easily. DataStax Enterprise on its own without Solr or Spark enabled is well-suited for long, complicated reports. The data model doesn't support joining multiple tables together, which is common in BI reporting.

I have additional thoughts about DataStax Enterprise, stating that the escalation process is excellent, the best I've seen. The support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through the data model exercise. I believe the subscription still comes with some hours to help get the data model reviewed.

Negative

I previously used Azure Cosmos DB as a different solution. I decided to switch from Azure Cosmos DB to DataStax Enterprise because I believe DataStax Enterprise is the best-in-class. There are some things that are different with the schema-less system, but I found that DataStax Enterprise is the easiest to implement while evaluating. The replication is on par or better than others in practice. We are evaluating Astra in our test environment, and that has additional benefits we are looking forward to using.

I have seen a return on investment. If not keeping current with updates, updating from an older major version to a newer major version can be a bit complicated and time-consuming, but DataStax Enterprise support will help us with this.

My experience with pricing, setup cost, and licensing indicates that the cost is a bit affordable, especially for my organization. However, for smaller organizations working under a tight budget, it might not be very affordable compared to other alternatives.

Before choosing DataStax Enterprise, I evaluated other options including Oracle Java SE, Microsoft Power BI, and MySQL.

I would rate DataStax Enterprise an eight out of ten.

I chose eight out of ten because it provides us with linear scale as well as multi-data center real-time replication of data such that we can maintain uptime even with the loss of multiple data centers, which is very crucial for our clients.

My main use case for DataStax Enterprise is handling the high-volume transactional data in a distributed system. I work on an application where we need to store and process a large amount of real-time data with low latency and high availability. We mainly use it for storing event-based data and ensuring that the system stays up even if some nodes go down. We also scale the application horizontally.

DataStax Enterprise handles our real-time event-based data requirements effectively. In my project, we have a system that logs every action a user takes, such as when the user clicks login, performs a click or transaction, or gets any API call. All of these are treated as events, and these events come in very high volume, thousands of events per second. We performed the data modeling for these, including user ID and event type. This allows for fast writes and efficient queries to get recent events for users.

Some of the best features DataStax Enterprise offers are services such as Cassandra, the built-in Cassandra instance that it provides, which has no single point of failure. It has support for an active-active architecture, and if a node goes down, it has a very robust fault tolerance allowing the systems to keep running. The massive scalability that it offers means the database can scale up to terabytes and petabytes easily, and it is also globally present across various regions. Additionally, it has high write performance, easily handling write-heavy workloads and is ideal for logging events, transactions, and user activities.

DataStax Enterprise positively impacts our organization by helping our developers write code that works very well and providing us with multi-region support.

DataStax Enterprise can provide other solutions that are well-suited for other use cases such as an auditing system or writing systems. Additionally, many other details can be provided for monitoring tools.

I gave DataStax Enterprise a rating of 8 out of 10 because there is still some room for improvement. For example, it can implement some cost optimization where the license can be expensive, and compared to open-source Cassandra, cost is a concern. Some other areas for improvement would be simplifying the setup, as the initial cluster setup is complex.

I have used DataStax Enterprise for around two to three months.

DataStax Enterprise is pretty stable.

DataStax Enterprise provides enough stability for our organization, and scaling can be done up to terabytes and petabytes.

The active-active architecture and fault tolerance of DataStax Enterprise helped my team significantly, as we had a multi-region deployment. One of our regions was India, and another was Singapore, meaning both regions handled reads and writes at the same time. Data is replicated, one in the India region and one in the Singapore region, with a replication factor of three. In this case, the active-active architecture helped us really scale and provide data to both Singapore and Indian users.

We find the customer support to be good.

I would rate the customer support nine out of 10.

This is a new implementation, and we did not have a distributed system before this.

My experience with pricing, setup cost, and licensing is that I feel the cost is a bit expensive compared to the open-source implementation of Cassandra, and the initial cluster setup is complex.

Before choosing DataStax Enterprise, we evaluated options from Azure and Google Cloud services, as well as other cloud services. We also considered MongoDB and PostgreSQL.

Some of the positive outcomes I see are that system stability improved a lot, there is no single point of failure, so downtime is reduced significantly, and the system stays up even when we face issues in a node. It handles the high traffic smoothly, with a thousand requests per second being managed well without major performance degradation, and the end users also see low latency.

My advice for others looking into using DataStax Enterprise is to do their metric analysis and cost and licensing analysis to check if DataStax Enterprise is suitable. If you have high-volume data and a write-heavy workload, then definitely go for DataStax Enterprise. I give this solution an overall rating of 8 out of 10.

My main use case for DataStax Enterprise is that Astra DB is a major feature of it. It is a NoSQL database, so you can store unstructured data in it, and it is very scalable. Initially, the setup is very easy, and they provide the flexibility to use any cloud and any region closer to your users' proximity.

Whenever I need to save data for my users, I call an API and the data gets saved to Astra DB. This is one of my workflows.

The ability to choose regions and cloud providers has positively affected my project because most of my application's users are based in the US. I chose AWS US East-1 for this reason.

DataStax Enterprise offers the best features including the ability to scale and the ability to choose the particular cloud provider. The pricing is very upfront, and you can see what each cloud costs to you. You can choose the region on which you want to host your database. The major factor is that if you choose the region of your database too far from your users, there will be latency, and you need to choose a location where most of your users are based.

DataStax Enterprise has positively impacted my organization because during research for a NoSQL database, developers are very positive about using DataStax Enterprise because of its really easy setup and the querying to the database is very efficient. You can use GraphQL to query, and it is very good.

I can share specific outcomes resulting from using DataStax Enterprise as we have been seeing an uptick in user adoption. Since the introduction of this, our users have jumped from around 20,000 to 50,000.

There is still room for improvement and DataStax Enterprise can definitely improve their UI.

I have been using DataStax Enterprise since 2022.

DataStax Enterprise is stable.

DataStax Enterprise's scalability is pretty scalable. It auto-scales, and as user demands increase, we can gather more compute resources from the cloud and speed up the servers.

I have not directly communicated with customer support, but one of my colleagues contacted them and found it to be pretty efficient.

I did not previously use a different solution. We started using DataStax Enterprise initially from the start of our application.

My experience with pricing, setup cost, and licensing is pretty good. I do not find any difficulty in it.

I have seen a return on investment as we have saved time to market. Earlier it was around 15 months, and we have been able to deploy and scale our application within 10 months. We have saved around five months.

My experience with pricing, setup cost, and licensing is pretty good. I do not find any difficulty in it.

Before choosing DataStax Enterprise, we evaluated other options, specifically MongoDB.

The latency for my US users is very minute, being around 200 milliseconds, so it is good.

DataStax Enterprise is very useful, and I found it very useful overall.

Per my use case, I found DataStax Enterprise pretty efficient and am content with it.

The advice I would give to others looking into using DataStax Enterprise is to choose their cloud provider clearly, as it will impact their cost and their reason.

I rate this product an 8 out of 10.

Main use cases involve building applications that need to handle large amounts of data with high speed and reliability, and real-time analytics, where fast data processing is important. One of the other use cases is storing time-series data such as logs or sensor data that needs to be available across different locations.

In my previous project, DataStax Enterprise's high availability and fault tolerance were crucial because we needed our application to be online all the time, even during maintenance and unexpected server issues. With DataStax Enterprise, we could add more nodes easily as our data grew, and we did not have performance problems. There were no failures thanks to the fault tolerance, so there was no downtime or compliance issues. Even when some nodes failed, the system automatically rerouted traffic and kept the service running.

Advanced security features such as encryption and access controls helped us protect sensitive data and meet internal security policies, which made it easier to prepare for compliance audits. I also appreciated that DataStax Enterprise offers strong monitoring and management tools, making it easier to keep track of system health and performance.

DataStax Enterprise has positively impacted my organization by helping us handle large amounts of data more easily and quickly, improving our system speed, and making our application more reliable. We can scale up or down based on our needs, saving us time and money, and the built-in security features have made our data safer and more secure from attackers and threats. Overall, it has made my team more productive and our customers happier.

I would suggest adding more automation features to DataStax Enterprise, which could reduce manual work even further.

My main use case for DataStax Enterprise is for search and transactions with a focus on availability.

A specific example of how I use DataStax Enterprise for search and transactions with high availability is that we have a multi-node cluster with disaster recovery across two data centers, specifically for our e-commerce website. This ensures that users do not face any downtime.

This is the main scenario I have regarding my use case with DataStax Enterprise.

The best feature DataStax Enterprise offers, in my opinion, is OpsCenter, which provides a user interface that allows us to manage our instance, take backups, and overall makes everything very much easily manageable.

OpsCenter makes things easier for me as we schedule backup jobs and monitor our cluster from there, which saves us from having to purchase another monitoring tool.

DataStax Enterprise has positively impacted my organization as we are now an e-commerce website that has never faced downtime, which helps our business to boom and significantly enhances our customer experience.

I can confirm that the outcomes of using DataStax Enterprise show that our database uptime has increased drastically to around 99.9%.

I believe that DataStax Enterprise could be improved by working more on making the OpsCenter user interface more user-friendly, particularly regarding the fonts and overall UI.

In addition to the needed improvements on the UI, I think DataStax support could also benefit from enhancements, particularly in terms of online resources.

I would appreciate improvements in customer support.

I have been using DataStax Enterprise for almost three years.

DataStax Enterprise is very stable.

The scalability of DataStax Enterprise is very good, and we are currently using two data centers.

Before DataStax Enterprise, we were using MongoDB, but we faced frequent database issues and a lack of uptime, which led us to switch.

I already mentioned that we evaluated MongoDB as our previous option before deciding on DataStax Enterprise.

We have seen a return on investment with DataStax Enterprise as we saved a lot of money and time, despite investing more on infrastructure; our ongoing business success with a 99.9% uptime helps us earn more.

My advice to others looking into using DataStax Enterprise is that if your budget allows and your use case fits, you can definitely go with it, as it is very flexible and will give you more uptime.

I would like to ask if there are any new updates or features coming for DataStax Enterprise.

I found this interview to be very interactive, and I appreciate it.

I give DataStax Enterprise an overall rating of 10.