We performed a comparison between Azure Data Factory and Vertica based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"In terms of my personal experience, it works fine."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"It's extremely consistent."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"I can do everything I want with SSIS and Azure Data Factory."
"We have been using drivers to connect to various data sets and consume data."
"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."
"Partition and join back to node are easy and simple for DBAs."
"I like the projection feature, which increases query performance."
"Vertica gives knowledgeable users and DBAs excellent tools for tuning."
"The feature I like best is performance. We use Red Tool and Red Job for the data warehouse and reporting. It's perfect. Performance is good, and it can return ad hoc queries very quickly. Of course, it's a cluster, so it's easy to scale."
"The product's initial setup phase is extremely simple."
"Allows us to take volumes and process them at a very high speed."
"The feature of the product that is most important is the speed. I needed a columnar database, and its speed is what it's built to do, and so that's what really does differentiate Vertica from its competitors."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"Data Factory's performance during heavy data processing isn't great."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"There aren't many third-party extensions or plugins available in the solution."
"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."
"One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility."
"Support is an area where it could get better."
"In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform."
"It would be great if this were a managed service in AWS."
"We are looking for a cheaper deployment for the solution. Although we did a lot of benchmarks, like Redshift. We tried Redshift, it didn't work. It didn't work out for us as well."
"I would personally like to see extended developer tooling suited to Vertica – think published PowerDesigner SQL dialect support."
"I have found that coding support could be simplified."
"In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics."
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Vertica is ranked 6th in Cloud Data Warehouse with 83 reviews. Azure Data Factory is rated 8.0, while Vertica is rated 8.2. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of Vertica writes " A user-friendly tool that needs to improve its documentation part". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and Oracle Exadata. See our Azure Data Factory vs. Vertica report.
See our list of best Cloud Data Warehouse vendors.
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
