Azure Cosmos DB vs. DataStax Enterprise

NoSQL platforms are very useful when it comes to security, speed, accuracy, high accessibility with high read and write power. Everything is managed under the cloud and we have the various capabilities of Azure and support for Microsoft products with us. Flexibility in price and variety of features, as well as real-time results, are some of the popular [features] of this platform.

Incentivized

DataStax has a good scalable option with multiple clusters and a good write rate. Cassandra also is improving and is an open-source technology that has good community support. The UI is also easy to understand and implement required functions.

Incentivized

• Turn-key geo-redundancy with multi-master writes is unprecedented and unparalleled in the industry!
• Guaranteed low latency makes Cosmos DB an excellent fit for most of our performance-intensive situations.
• The tunable consistency model simplifies so many challenges in distributed systems engineering that otherwise require advanced knowledge of computer science topics. I continue to be impressed at how Cosmos DB has abstracted away so much complexity.

Incentivized

• Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
• Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
• Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
• Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.

Incentivized

• When searching by default, it is case sensitive, which must be changed by default
• In many ways, the price should be more flexible according to the requested facilities, because the price is very expensive for startup companies.
• It is not fully compatible with most common Streaming Analytics tools applications and developers should be worked on it

Incentivized

• Cassandra is a bit difficult to learn and understand
• The costs are slightly higher for our company
• Hardware requirement is moderate to high at the beginning

Incentivized

It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.

Incentivized

We will continue to use it because it scales well with commodity hardware and we are satisfied with the documentation and support.

Incentivized

Like I said, Cosmos is the way to go. From all of the services that Azure has, Cosmos is very robust in terms of usability. It's ever-evolving and integrates with other applications seamlessly. The interface is pretty easy to understand. I implemented various solutions for my company and Cosmos was one of them.

Incentivized

There is a bit of a learning curve and tasks that are simple in traditional RDBMS systems can be complicated with DataStax Enterprise but once you get the hang of denormalizing data and getting the data model correct DataStax Enterprise is very usable. Usability from the developer's standpoint is very simple - the complication is on the architecture side with the data model.

The support team is very responsive and we are generally satisfied with Microsoft support, in my opinion support team of a product and service is just as valuable as its quality and performance. Telephone answering, 24-hour hotline, email support and ticketing are excellent.

Incentivized

We have had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.

Azure Cosmos DB for MongoDB is more affordable than many other solutions and works incredibly well if you're within the Azure ecosystem.

Incentivized

I believe DataStax Enterprise is the best in class. There are some things that are different with the schema-less systems but I found DataStax Enterprise 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.

• Expensive but works if your infra is on Azure data center.
• No latency and nearly no downtime.
• Takes time for end users to adapt.

Incentivized

• Highly Scalable Database, Highly Available Services, and Platforms.
• High Performance, Low Latency and Highest throughput across varying workloads.
• Configured, Tuned and Monitored correctly works to provide the best user experience!
• Negative: Maintenance and Debugging Corner Cases

Incentivized