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 are powerful data management solutions competing in analytics and big data processing. Vertica appears to have the upper hand in providing high-performance analytics and SQL support, while Hadoop excels in flexibility and handling vast unstructured data cost-effectively.
Features: Vertica offers advanced data compression, scalability, and SQL standard query support. Its in-memory storage and clustering without shared storage enhance performance and maintenance. Hadoop provides exceptional data storage capabilities through HDFS, managing massive datasets at low cost. It integrates well with tools like Spark and Kafka, highlighting its scalability and flexibility.
Room for Improvement: Vertica users report the need for better transaction handling, enhanced SQL optimization, and improved developer tools. Hadoop requires advancements in real-time processing, a more user-friendly interface, and better integration tools, with its complexity necessitating significant expertise.
Ease of Deployment and Customer Service: Vertica supports various deployments, including on-premises and cloud, with variable technical support noted for its knowledgeability. Hadoop also offers diverse deployment models but often requires external expertise due to its complexity, leading to mixed technical support experiences.
Pricing and ROI: Vertica uses a simple data size-based licensing model, offering good ROI despite perceived high costs due to its speed and analytical capabilities. Hadoop's open-source nature makes it cost-effective, presenting substantial savings, though the required expertise for implementation might impact overall cost-effectiveness.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
It is a distributed file system and scales reasonably well as long as it is given sufficient resources.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
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.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
| Product | Market Share (%) |
|---|---|
| Apache Hadoop | 4.3% |
| OpenText Analytics Database (Vertica) | 6.9% |
| Other | 88.8% |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 8 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 23 |
| Large Enterprise | 38 |
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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