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
OpenText Analytics Database (Vertica) and Apache Hadoop both compete in the data analytics and big data processing category. OpenText Analytics Database (Vertica) appears to have an edge due to its superior storage solutions, read speed, and integration capabilities, as reflected in user feedback.
Features: OpenText Analytics Database (Vertica) offers Massively Parallel Processing (MPP), columnar storage, and excellent read speed. Users highlight its scalability, integration with Power BI and Tableau, and cost-effective data storage options like Amazon S3. Apache Hadoop is praised for its open-source nature, efficient handling of large data volumes, and integrated ecosystem for unstructured data processing, beneficial for AI and ML applications.
Room for Improvement: OpenText Analytics Database (Vertica) needs better community support, enhanced dynamic projections, and faster data updates. Improved documentation and third-party tool integration are also desired. Apache Hadoop could improve user-friendliness, security measures, and real-time processing. Enhancing the UI and reducing complexity in handling large datasets are common user suggestions.
Ease of Deployment and Customer Service: OpenText Analytics Database (Vertica) is deployed effectively in both cloud and on-premises environments, with streamlined customer support but varying technical assistance quality. Apache Hadoop offers versatile deployment options but faces challenges with support responsiveness and community engagement, indicating a need for better customer service.
Pricing and ROI: OpenText Analytics Database (Vertica) is considered pricey but provides substantial ROI with efficient storage and time-saving features, justified by its capabilities. Apache Hadoop presents lower direct costs being open-source, but potential licensing fees with some distributions could increase costs, offering significant value for large-scale data enterprises but becoming costly for smaller setups. Both solutions deliver solid ROI, with Vertica being cost-efficient and Hadoop effective for extensive dataset handling.
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.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
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.
It is a distributed file system and scales reasonably well as long as it is given sufficient resources.
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.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
OpenText Analytics Database (Vertica) is very stable.
The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it.
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.
The pricing for OpenText Analytics Database (Vertica) is somewhat on the higher side for the license.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
I assess Apache Hadoop's fault tolerance during hardware failures positively since we have hardware failover, which works without problems.
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.
| Product | Mindshare (%) |
|---|---|
| OpenText Analytics Database (Vertica) | 5.7% |
| Apache Hadoop | 3.3% |
| Other | 91.0% |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 8 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 23 |
| Large Enterprise | 43 |
Apache Hadoop provides a scalable, cost-effective open-source platform capable of handling vast data volumes with features like HDFS, distributed processing, and high integration capabilities.
Apache Hadoop is known for its distributed file system HDFS, which supports large data volumes efficiently. Its open-source nature allows cost-effective scalability and compatibility with tools like Spark for enhanced analytics. While it offers significant processing power, areas for improvement include user-friendliness, interface design, security measures, and real-time data handling. Users benefit from data storage for structured and unstructured data, facilitated by its distributed processing architecture. Data replication ensures fault tolerance, while its capability to integrate with tools like Apache Atlas and Talend highlights its versatility.
What are the key features of Apache Hadoop?Industries leverage Apache Hadoop for Big Data analytics, data lakes, ETL tasks, and enterprise data hubs, handling unstructured and structured data from IoT, RDBMS, and real-time streams. Its applications extend to data warehousing, AI/ML projects, and data migration, employing tools like Apache Ranger, Hive, and Talend for effective data management and analysis.
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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