

Microsoft Parallel Data Warehouse and OpenText Analytics Database (Vertica) both excel in the data analytics category, catering to large organizations seeking robust data management. Vertica seems to have an edge due to its superior speed and analytics capabilities, making it more suitable for large-scale data analytics tasks.
Features: Microsoft Parallel Data Warehouse offers SQL support for versatile data management, integration with Microsoft products, and strong business intelligence capabilities. OpenText Analytics Database (Vertica) provides fast query response times, robust analytics, and effective data compression, enhancing performance in complex data analysis.
Room for Improvement: Microsoft Parallel Data Warehouse could improve on cost, BI tool compatibility, and error messaging. Its scalability and cloud features need enhancement. Vertica's documentation and management tools require refinement, and users seek better workload management and SQL optimizer enhancements.
Ease of Deployment and Customer Service: Microsoft Parallel Data Warehouse can be complex to deploy but offers reliable customer service. Vertica provides extensive deployment flexibility and robust technical support, though deployment simplicity could improve for both systems.
Pricing and ROI: Microsoft's pricing is high but considered fair for large organizations, yielding a robust ROI. Vertica's licensing by data size proves cost-effective, with users justifying its cost for analytic performance. Both solutions deliver notable ROI through integration and data management capabilities.
I would rate my experience with technical support around six on a scale of 1 to 10 because I have not had a particular experience with technical support.
I give the scalability an eight out of ten, indicating it scales well for our needs.
As a consultant, we hire additional programmers when we need to scale up certain major projects.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
Addressing the cost would be the number one area for improvement.
It would be better to release patches less frequently, maybe once a month or once every two months.
The ETL designing process could be optimized for better efficiency.
Microsoft Parallel Data Warehouse is very expensive.
The columnstore index enhances data query performance by using less space and achieving faster performance than general indexing.
The biggest advantage of Microsoft Parallel Data Warehouse is the possibility to stop or pause the service because it can be very expensive.
There's a feature that allows users to set alerts on triggers within reports, enabling timely actions on pending applications and effectively reducing waiting time.
| Product | Market Share (%) |
|---|---|
| OpenText Analytics Database (Vertica) | 5.8% |
| Microsoft Parallel Data Warehouse | 1.7% |
| Other | 92.5% |


| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 23 |
| Large Enterprise | 38 |
The traditional structured relational data warehouse was never designed to handle the volume of exponential data growth, the variety of semi-structured and unstructured data types, or the velocity of real time data processing. Microsoft's SQL Server data warehouse solution integrates your traditional data warehouse with non-relational data and it can handle data of all sizes and types, with real-time performance.
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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