We performed a comparison between Apache Hadoop and Aster Data Map Reduce 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 solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"The tool's stability is good."
"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics."
"One valuable feature is that we can download data."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"We selected Apache Hadoop because it is not dependent on third-party vendors."
"It's good for storing historical data and handling analytics on a huge amount of data."
"The most valuable feature is the ease of uploading data from multiple sources."
"It's stable and reliable."
"The ease of deployment is useful so clients are up and running quickly in comparison to other products."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."
"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."
"The stability of the solution needs improvement."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"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."
"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."
"Since it is an open-source product, there won't be much support."
"It would be good to have more advanced analytics tools."
"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."
"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."
Apache Hadoop is ranked 5th in Data Warehouse with 34 reviews while Aster Data Map Reduce is ranked 19th in Data Warehouse with 3 reviews. Apache Hadoop is rated 7.8, while Aster Data Map Reduce is rated 7.4. The top reviewer of Apache Hadoop writes "Handles huge data volumes and create your own workflows and tables but you need to have deeper knowledge". On the other hand, 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 ". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Aster Data Map Reduce is most compared with . See our Apache Hadoop vs. Aster Data Map Reduce report.
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We monitor all 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.
