We performed a comparison between Aster Data Map Reduce and Vertica based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse."The most valuable feature is the ease of uploading data from multiple sources."
"The ease of deployment is useful so clients are up and running quickly in comparison to other products."
"It's stable and reliable."
"The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful."
"Vertica gives knowledgeable users and DBAs excellent tools for tuning."
"Partition and join back to node are easy and simple for DBAs."
"The product's initial setup phase is extremely simple."
"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."
"I don't need any special hardware. I can use commodity hardware, which is nice to have in a commercial solution."
"Eighty percent of the ETL operations have improved since implementing this solution."
"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."
"It is hard for some of our users to set up rules for cleansing and transforming data, so this is something that could be improved."
"From my perspective, it would be good if they gave better ITIN/R plugins to use the data for AI modeling, or data science modeling. We can do it now; however, it could be more elegant in terms of interfacing."
"There are some ways that the handling of unstructured data could be improved."
"I believe the installation process could be streamlined."
"The documentation of Vertica is an area with shortcomings where improvements are required."
"I think they need an easy client so that you can write queries easily, but it's not necessarily a weak point. I think some users would need them."
"The integration with AI has room for improvement."
"The geospatial functionality could be designed better."
"They could improve the integration and some of the features in the cloud version."
"Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down."
"The integration of this solution with ODI could be improved."
Aster Data Map Reduce is ranked 19th in Data Warehouse with 3 reviews while Vertica is ranked 4th in Data Warehouse with 82 reviews. Aster Data Map Reduce is rated 7.4, while Vertica is rated 8.4. The top reviewer of Aster Data Map Reduce writes "Has good base product functionality of data storage and analytics but there should be an option to use it on the cloud ". On the other hand, the top reviewer of Vertica writes " A user-friendly tool that needs to improve its documentation part". Aster Data Map Reduce is most compared with , whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and Oracle Exadata.
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