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 database solutions category. User reviews suggest MongoDB has the upper hand in affordability and support, while Vertica stands out in advanced analytics and performance.
Features: MongoDB offers fast searches, scalability, and a developer-friendly environment, primarily supporting JSON document storage. Vertica is known for its quick response times on complex queries due to columnar storage, efficient projections, and parallel processing capabilities.
Room for Improvement: MongoDB users suggest enhanced security, indexing stability, and better hybrid environment integration. Vertica could improve workload management, documentation, and developer tool integration, as well as manage resource demands during peak loads.
Ease of Deployment and Customer Service: MongoDB is versatile in hybrid cloud deployment and has a strong community, although enterprise support could be faster. Vertica is versatile across platforms but lacks intuitive management tools and robust technical support. Both could benefit from enhanced customer engagement.
Pricing and ROI: MongoDB is valued for its open-source model and cost-effectiveness, appealing to small to medium businesses with low TCO. Vertica’s pricing is competitive, based on data size rather than node count, but can be pricey for large implementations. While MongoDB shows performance improvement for ROI, Vertica’s pricing aligns with its analytics capabilities, yet both need clearer ROI visibility.
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.
I saved a lot of money because the storage was on a cheaper alternative and was not directly on OpenText Analytics Database (Vertica), but on S3.
The time we used to take with our earlier databases has reduced to one-tenth of what was there earlier, which is a positive outcome that can be converted to financial metrics in terms of return on investment.
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.
Throughout this process, customer support was outstanding, and we had a person actively supporting us from the OpenText Analytics Database (Vertica) team for our use case.
Overall, our experience with OpenText Analytics Database (Vertica) customer support has been good and reliable.
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.
We have experienced easy horizontal scaling, consistent query performance as data grew, and the ability to handle large analytic workloads.
OpenText Analytics Database (Vertica) has very good scalability.
OpenText Analytics Database (Vertica) can scale to a great extent.
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced.
OpenText Analytics Database (Vertica) is very stable.
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.
Smarter automatic projection management is needed with more intelligence, auto projection creation, automatic optimization, and reduced manual testing with better workload management.
Projections could be made more dynamic, and if they could find a faster way to update, insert, and delete data, that would also be helpful.
OpenText Analytics Database (Vertica) does not have a cloud-based UI that Snowflake has, which features a very good comprehensive GUI for querying and analyzing data.
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 pricing for OpenText Analytics Database (Vertica) is somewhat on the higher side for the license.
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.
I can use it in Eon Mode in which I can store the data in cheaper storage such as Amazon S3 and have different compute nodes.
Projection and columnar storage are the most valuable features because they dramatically improve query performance and reduce the need for index management.
The best features that OpenText Analytics Database (Vertica) offers are mainly the parallel processing, ETL capabilities, and the multi-cloud features which are very handy to use.
| Company Size | Count |
|---|---|
| Small Business | 36 |
| Midsize Enterprise | 13 |
| Large Enterprise | 39 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 23 |
| Large Enterprise | 43 |
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.
OpenText Analytics Database Vertica enhances data processing with swift queries, scalability, and efficient compression, optimally managing enterprise-level data with minimal storage.
OpenText Analytics Database Vertica provides high availability clustering, columnar storage, and parallel processing to deliver fast data ingestion and real-time insights. Projections improve performance and simplify query tuning. The Management Console assists with administration, and integration with BI tools streamlines analytics. Adapted for handling large data volumes, Vertica supports data warehousing, ETL, geospatial analysis, and operational reporting across sectors such as media, finance, and telecom.
What are the most important features of OpenText Analytics Database Vertica?Organizations in media, finance, and telecom rely on Vertica's capabilities to integrate with Power BI and Tableau, facilitating advanced data analytics and machine learning for business improvements. Its support for ETL processes, real-time processing, and geospatial analysis positions Vertica as critical for operational reporting and decision support systems.
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