Apr 19, 2020
I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following
https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
MongoDB Enterprise Advanced and OpenText Analytics Database (Vertica) compete in the data management and analytics category. Vertica has the upper hand, largely due to its robust features geared towards extensive data analytics, which are appreciated at the price point for large-scale analytics applications.
Features: MongoDB is recognized for its scalability, flexibility, and developer-friendly approach, along with its effective handling of unstructured data and robust security. These attributes make it suitable for applications needing to manage JSON formats, like in healthcare. In contrast, Vertica provides exceptional analytical capabilities, fast query performance, and efficient data storage using a columnar architecture. Its ability to manage large-scale analytics and concurrent access is distinctive, complemented by strong aggregation functions and real-time analytics.
Room for Improvement: MongoDB could enhance enterprise integration, indexing capabilities, and documentation. Security setup guidance needs attention, as does scaling cost management. For Vertica, improvements in handling high transaction volumes, simplification of data management, and documentation are desired. Users also recommend better support for smaller setups and more intuitive management tools.
Ease of Deployment and Customer Service: MongoDB offers diverse deployment options like public, private, and hybrid clouds. It's known for easy setup and has strong community support, although official technical support quality can vary with subscription tiers. Vertica also supports similar deployment options, with strong official support but requires nuanced resource management to optimize usage. Users seek more intuitive setup processes and enhanced documentation.
Pricing and ROI: MongoDB’s open-source version aids cost savings, but enterprise options are considered steep by some. Despite the cost, performance and feature set provide solid ROI. Vertica’s data size-based pricing, though seen as expensive, is justified by its performance. The licensing flexibility for varied business needs adds value, especially for extensive analytics workloads.
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.
We have received fairly good support whenever we reached out to the technical teams; they were prompt.
CosmoDB is better for auto-scale.
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.
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced.
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.
While solutions for other databases like SQL or PostgreSQL already exist, MongoDB requires additional integrations for developing AI solutions.
From the AWS standpoint, if robust integration and data warehouse integration specific tools are added in the advanced suite, that would definitely be helpful.
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.
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.
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.
MongoDB has definitely helped us improve our network monitoring and reporting dashboard.
| Company Size | Count |
|---|---|
| Small Business | 35 |
| Midsize Enterprise | 13 |
| Large Enterprise | 38 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 23 |
| 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.
OpenText Analytics Database Vertica is known for its fast data loading and efficient query processing, providing scalability and user-friendliness with a low cost per TB. It supports large data volumes with OLAP, clustering, and parallel ingestion capabilities.
OpenText Analytics Database Vertica is designed to handle substantial data volumes with a focus on speed and efficient storage through its columnar architecture. It offers advanced performance features like workload isolation and compression, ensuring flexibility and high availability. The database is optimized for scalable data management, supporting data scientists and analysts with real-time reporting and analytics. Its architecture is built to facilitate hybrid deployments on-premises or within cloud environments, integrating seamlessly with business intelligence tools like Tableau. However, challenges such as improved transactional capabilities, optimized delete processes, and better real-time loading need addressing.
What features define OpenText Analytics Database Vertica?OpenText Analytics Database Vertica's implementation spans industries such as finance, healthcare, and telecommunications. It serves as a central data warehouse offering scalable management, high-speed processing, and geospatial functions. Companies benefit from its capacity to integrate machine learning and operational reporting, enhancing analytical capabilities.
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