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."Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"Hadoop File System is compatible with almost all the query engines."
"It's good for storing historical data and handling analytics on a huge amount of data."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."
"The most valuable feature is the database."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"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."
"It would be good to have more advanced analytics tools."
"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."
"Hadoop's security could be better."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"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 6th in Data Warehouse with 34 reviews while Aster Data Map Reduce is ranked 20th 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.
