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."Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"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."
"The most valuable feature is the database."
"It's stable and reliable."
"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."
"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 solution is very expensive."
"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."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"It could be more user-friendly."
"The upgrade path should be improved because it is not as easy as it should be."
"There are some ways that the handling of unstructured data 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."
"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 32 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 "A file system for data collection that contains needed information and files". 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 .
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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.
