Cloudera Distribution for Hadoop and MongoDB Enterprise Advanced compete in the big data ecosystem. Cloudera leads in cluster management and integration, while MongoDB excels in flexibility and scalability for handling unstructured data.
Features: Cloudera is renowned for its granular security through Sentry, fast data processing with Impala, and cluster oversight via Cloudera Manager. It supports Hadoop ecosystem functionalities through tools like HiveQL and Pig. MongoDB is appreciated for its JSON-based document storage, easy scalability, and developer-friendly interface, offering seamless data manipulation and integration with other tools.
Room for Improvement: Cloudera could enhance its stability, performance, and pricing structure while also improving integration capabilities. Support services and comprehensive documentation are additional areas needing attention. MongoDB users suggest enhancements in performance, security, and relational database integration, along with simplifying query writing for SQL users.
Ease of Deployment and Customer Service: Cloudera is typically deployed on-premises, suiting enterprises with existing infrastructure, but mixed reviews exist about its support responsiveness. MongoDB offers more versatile deployment options across cloud environments and is often praised for its effective support and robust community support.
Pricing and ROI: Cloudera's pricing can be prohibitive for small and medium businesses, though it provides significant ROI for larger enterprises with resources to leverage its comprehensive features. MongoDB's open-source model offers a cost-effective entry point, and its enterprise edition, while pricier, competes effectively with traditional database solutions like Oracle, particularly benefiting smaller organizations.
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.
The technical support is quite good and better than IBM.
We have received fairly good support whenever we reached out to the technical teams; they were prompt.
In CosmoDB, the scalability is much better than with the MongoDB ReplicaSet models.
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.
MongoDB is highly scalable.
We faced challenges but overcame those challenges successfully.
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced.
Integrating with Active Directory, managing security, and configuration are the main concerns.
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.
It can be deployed on-premises, unlike competitors' cloud-only solutions.
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.
This is the only solution that is possible to install on-premise.
When the database receives numerous requests, it has to perform. Those threshold limits we come to know, and then automatically these memory enhancement advanced features are configured so that during high demand periods, memory automatically increases to cater to the incoming advanced requests and volume of requests.
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.
| Product | Market Share (%) |
|---|---|
| MongoDB Enterprise Advanced | 16.2% |
| Cloudera Distribution for Hadoop | 3.0% |
| Other | 80.8% |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 9 |
| Large Enterprise | 31 |
| Company Size | Count |
|---|---|
| Small Business | 35 |
| Midsize Enterprise | 13 |
| Large Enterprise | 38 |
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.
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