Cloudera Distribution for Hadoop and MongoDB Enterprise Advanced offer data management solutions in the enterprise sector. Cloudera has the upper hand in data processing and integration features, while MongoDB excels in flexibility and developer-friendly attributes.
Features: Cloudera offers Hadoop integration, centralized management with Cloudera Manager, and security features like Sentry. MongoDB's features include a schemaless architecture, robust JSON capabilities, and a sharding system for flexibility and ease in development.
Room for Improvement: Cloudera users point out the need for better stability and speed, especially in HBase and Spark. Documentation and AI integration could be improved. MongoDB could enhance sharding performance, transaction handling, and default security practices.
Ease of Deployment and Customer Service: Cloudera is typically deployed on-premises, while MongoDB is favored for its public and hybrid cloud deployments. MongoDB is easier to deploy, and both brands receive positive feedback on customer support, though Cloudera's support responsiveness could improve.
Pricing and ROI: Cloudera is considered costly, impacting scalability choices. MongoDB provides a free community edition and competitive pricing for enterprise offerings, appealing to growing enterprises. Both offer significant ROI, but Cloudera may be more expensive for smaller businesses.
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.
I think they resolved it, but it was very long.
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 have to pay approximately 2,000 euros per month for MongoDB.
We use the free version of MongoDB, so there are no licensing costs.
On DigitalOcean, they have strict routing. You have to whitelist an IP address, or you risk getting DDoS.
This is the only solution that is possible to install on-premise.
MongoDB's dashboards offer more functionalities and allow you to create a dashboard with MongoDB database data.
We always use Redis for the in-memory storage engine with MongoDB Enterprise Advanced.
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.
| Product | Mindshare (%) |
|---|---|
| MongoDB Enterprise Advanced | 11.3% |
| Cloudera Distribution for Hadoop | 6.1% |
| Other | 82.6% |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 9 |
| Large Enterprise | 32 |
| Company Size | Count |
|---|---|
| Small Business | 36 |
| Midsize Enterprise | 13 |
| Large Enterprise | 39 |
Cloudera Distribution for Hadoop provides a comprehensive platform for efficient data management and analytics, integrating advanced analytics tools with enterprise-grade security and hybrid cloud support.
Designed for handling vast datasets, Cloudera Distribution for Hadoop facilitates seamless data processing through its components such as Hive, Pig, and Spark. It supports both structured and unstructured data management with robust scalability and powerful data handling capabilities. While the latest version focuses on enhancing speed and integration, challenges remain with HBase stability and processing in Cloudera 5 clusters. Organizations leverage it for big data management tasks like data warehousing, log analytics, and real-time data processing using tools like Hadoop and Spark.
What are the key features of Cloudera Distribution for Hadoop?In industries such as finance, retail, and healthcare, Cloudera Distribution for Hadoop is implemented to enhance data-driven decision-making and operational efficiency. It aids in processing large volumes of data for analytics, data warehousing, and infrastructure building. Companies utilize it to streamline machine learning and log analytics, serving as a data lake for preprocessing substantial datasets.
MongoDB Enterprise Advanced offers scalability, speed, and flexible schema design, ideal for managing large data volumes. Its extensive documentation and object retrieval capabilities support cloud deployment with in-memory storage and robust security features.
Designed to handle large volumes of unstructured data, MongoDB Enterprise Advanced supports big data analysis and document management across different data formats. The aggregation framework enables deep data analysis while dynamic structures allow seamless schema changes. JavaScript-based query execution enhances development flexibility and the document-based format simplifies data storage and retrieval. Despite some performance, integration, and security concerns, it remains favored for IoT platforms, web applications, and transaction data storage. Challenges with complex joins, scalability, and sharding are noted, along with the need for refined documentation and improved compatibility with Microsoft Windows. Users call for larger data operation support, Google BigQuery integration, and improvements in stability and certified container images.
What are the most important features of MongoDB Enterprise Advanced?Industries like telecom, banking, healthcare, and logistics implement MongoDB Enterprise Advanced for its flexibility, scalability, and compatibility with different data formats. It's particularly suited for IoT platform development, web application support, transaction data storage, and integration of front-end and back-end systems, making it a valuable asset in dynamic environments.
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