We performed a comparison between Microsoft Parallel Data Warehouse and Vertica based on real PeerSpot user reviews.
Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature is the business intelligence (BI) part of it."
"It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time."
"It is not a pricey product compared to other data warehouse solutions."
"Data collection and reporting are valuable features of the solution."
"The solution has been reliable."
"It is a stable solution...It is a scalable solution."
"Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time."
"I like Data Warehouse's data integrity features. Data integrity is what databases are made for as opposed to spreadsheets."
"The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful."
"The performance is very good and the aggregate records are fast."
"The most valuable feature of Vertica is the ability to receive large aggregations at a very quick pace. The use case of subclusters is very good."
"Any novice user can tune vertical queries with minimal training (or no training at all)."
"The solution is quick, has good compression data, and is not expensive."
"I appreciate the flexibility offered by Vertica's projections. It allows for modifying the primary projection without altering the tables, which helps to optimize queries without the need to modify the underlying data."
"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."
"I have found the solution to be scalable."
"It needs more compatibility with common BI tools."
"It could offer more development across the solution."
"In the future I would love to see a slightly better automation engine, just for the data integration layer, to make it slightly easier for end-users or junior developers to get involved in incremental updating."
"It could be made more user-friendly for business users which would increase the user base."
"The product must provide more frequent updates."
"SQL installation is pretty tricky. The scalability and customer support also should be improved."
"The reporting for certain types of data needs to be improved."
"We find the cost of the solution to be a little high."
"Vertica's native cloud support could be improved, and its installation could be made easier."
"It needs integration with multiple clouds."
"They could improve on customer service."
"In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform."
"The integration with AI has room for improvement."
"Some of our small to medium-sized customers would like to see containerization and flexibility from the deployment standpoint."
"Suboptimal projection design causes queries to not scale linearly."
"When it is about to reach the maximum storage capacity, it becomes slow."
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Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews while Vertica is ranked 4th in Data Warehouse with 83 reviews. Microsoft Parallel Data Warehouse is rated 7.6, while Vertica is rated 8.2. The top reviewer of Microsoft Parallel Data Warehouse writes "An easy to setup tool that allows its users to write stored procedure, making it a scalable product". On the other hand, the top reviewer of Vertica writes " A user-friendly tool that needs to improve its documentation part". Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA, VMware Tanzu Greenplum and Snowflake, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and Oracle Exadata. See our Microsoft Parallel Data Warehouse vs. Vertica report.
See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.
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