We performed a comparison between Apache Hadoop and Aster Data Map Reduce based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse."The best thing about this solution is that it is very powerful and very cheap."
"Hadoop is extensible — it's elastic."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"The most valuable feature is the database."
"The scalability of Apache Hadoop is very good."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"It's good for storing historical data and handling analytics on a huge amount of data."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"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."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"I would like to see more direct integration of visualization applications."
"General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error."
"Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them."
"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."
"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."
"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."
"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."
"There are some ways that the handling of unstructured data could be improved."
Apache Hadoop is ranked 5th in Data Warehouse with 11 reviews while Aster Data Map Reduce is ranked 19th in Data Warehouse with 1 review. Apache Hadoop is rated 7.8, while Aster Data Map Reduce is rated 7.4. The top reviewer of Apache Hadoop writes "Has good processing power and speed and is capable of handling large volumes of data and doing online analysis". On the other hand, the top reviewer of Aster Data Map Reduce writes "Easy to set up with fast data input but needs more documentation surrounding their on-premises offering". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Azure Data Factory, Oracle Exadata, Snowflake and Teradata, whereas Aster Data Map Reduce is most compared with .
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