

DataStax Enterprise and MongoDB Enterprise Advanced compete in the database management solutions market. MongoDB Enterprise Advanced seems to have the upper hand due to its rich features and overall performance capabilities.
Features: DataStax Enterprise offers robust scalability, built-in analytics, and strong support for hybrid cloud environments. MongoDB Enterprise Advanced provides flexible schema designs, powerful aggregation queries, and support for diverse data models.
Ease of Deployment and Customer Service: DataStax Enterprise ensures seamless integration with cloud platforms and an easy deployment process. It is known for quick and effective issue resolution. MongoDB Enterprise Advanced also supports cloud environments and is praised for its comprehensive documentation and community resources.
Pricing and ROI: DataStax Enterprise has higher initial setup costs but offers competitive ROI through strong features and support for long-term benefits. MongoDB Enterprise Advanced features lower setup costs and a favorable ROI due to its adaptable licensing and community support.
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.
Earlier it was around 15 months, and we have been able to deploy and scale our application within 10 months.
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.
Actually, with MongoDB, it's difficult to calculate the return on investment; it's too expensive for our use.
I would say we see value in money and return on investment with MongoDB Enterprise Advanced.
Real-time transaction processing, both reads and writes, is where DataStax Enterprise shines the most.
I would rate the customer support nine out of 10.
one of my colleagues contacted them and found it to be pretty efficient
We have received fairly good support whenever we reached out to the technical teams; they were prompt.
I think they resolved it, but it was very long.
Overall, we saw a decrease in operational costs due to better resource usage and less manual work, which made my team more efficient and allowed us to focus on new projects.
DataStax Enterprise's scalability is very fast with linear scalability and hence is very scalable.
The active-active architecture helped us really scale and provide data to both Singapore and Indian users.
In CosmoDB, the scalability is much better than with the MongoDB ReplicaSet models.
MongoDB is highly scalable.
Overall, on a scale of one to ten, I would rate MongoDB an eight; it's mostly because we're still running a monolithic environment on old hardware, so there are some limitations with read-write access.
DataStax Enterprise provides enough stability for our organization, and scaling can be done up to terabytes and petabytes.
After using DataStax Enterprise, our system downtime dropped by approximately 40%, helping us avoid lost revenue.
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced.
Better compatibility with prior versions in terms of codebases should also be improved.
For example, it can implement some cost optimization where the license can be expensive, and compared to open-source Cassandra, cost is a concern.
More built-in monitoring and alerting tools would make it easier to find and fix problems quickly.
While solutions for other databases like SQL or PostgreSQL already exist, MongoDB requires additional integrations for developing AI solutions.
We have not contracted the security options in our contract because they're too expensive; thus, we implement just encrypted databases and not the security pack.
From the AWS standpoint, if robust integration and data warehouse integration specific tools are added in the advanced suite, that would definitely be helpful.
For smaller organizations working under a tight budget, it might not be very affordable compared to other alternatives.
We use the free version of MongoDB, so there are no licensing costs.
We have to pay approximately 2,000 euros per month for MongoDB.
For a small company, the cost of MongoDB Enterprise Advanced is reasonable, but for heavy data usage, we see a little bit of cost pressure but it's acceptable.
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.
I can confirm that the outcomes of using DataStax Enterprise show that our database uptime has increased drastically to around 99.9%.
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.
It offers flexibility in schema adaptation, allowing us to change the schema and add new data points.
In ReplicaSet, it's acceptable, but if your workload needs more performance, and you must pass to a Sharding model, it becomes complicated in MongoDB; in Cosmos DB, however, it's simple.
MongoDB has definitely helped us improve our network monitoring and reporting dashboard.
| Product | Mindshare (%) |
|---|---|
| MongoDB Enterprise Advanced | 13.2% |
| DataStax Enterprise | 3.4% |
| Other | 83.4% |

| Company Size | Count |
|---|---|
| Small Business | 2 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 36 |
| Midsize Enterprise | 13 |
| Large Enterprise | 39 |
DataStax Enterprise offers a high-performance, scalable database solution designed for modern data requirements, supporting a wide array of use cases that demand real-time analytics and robust security.
Focusing on delivering powerful distributed databases, DataStax Enterprise integrates the open-source foundation of Apache Cassandra, delivering enhanced features for enterprises. It supports mission-critical applications at scale, providing real-time query capabilities and fault tolerance. Designed with high availability and operational efficiency, it supports complex data models and simplifies management with advanced tools for monitoring and repair.
What are the standout features of DataStax Enterprise?In industries such as finance, telecommunications, and retail, DataStax Enterprise is implemented to handle immense data workloads, often leveraging its capabilities for fraud detection, personalized customer experiences, and real-time decision-making. Its deployment in these sectors highlights its adaptability and performance in demanding environments.
MongoDB Enterprise Advanced is a comprehensive platform renowned for its scalability, user-friendliness, and high performance, underpinned by its flexible document-based storage and open-source model. JSON compatibility, clustering, and security elevate its standing among professionals.
The platform facilitates efficient data management through developer-friendly tools and a strong aggregation framework. MongoDB’s no-schema requirement, supported by community expertise, underlines its adaptability. While its sharding capabilities and affordably support large data volumes, there are aspects such as security enhancement and enterprise tool integration that need attention. Indexing and query optimization pose challenges, alongside high costs. Improvements in analytics and UI could advance its infrastructure further.
What are the key features of MongoDB Enterprise Advanced?Industries leverage MongoDB Enterprise Advanced for significant roles in data storage within IoT platforms, healthcare apps, public service monitoring, and big data analytics. Companies in logistics and telecommunications find it instrumental for business process management and video content management, benefiting from its seamless integration and unstructured data support.
We monitor all NoSQL Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.