We performed a comparison between Apache Hadoop and Oracle Big Data Appliance 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."Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"The most valuable feature is the database."
"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."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."
"It's open-source, so it's very cost-effective."
"As compared to Hive on MapReduce, Impala on MPP returns results of SQL queries in a fairly short amount of time, and is relatively fast when reading data into other platforms like R."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."
"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."
"This is a comprehensive solution that is easy to deploy."
"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."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"I would like to see more direct integration of visualization applications."
"The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."
"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."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"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."
"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
"The product should be simplified for the average user."
Apache Hadoop is ranked 6th in Data Warehouse with 34 reviews while Oracle Big Data Appliance is ranked 14th in Data Warehouse. Apache Hadoop is rated 7.8, while Oracle Big Data Appliance is rated 8.0. 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 Oracle Big Data Appliance writes "Fast, and you don't need technical expertise to use it and produce results". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Vertica, whereas Oracle Big Data Appliance is most compared with Oracle Exadata and Microsoft Azure Synapse Analytics. See our Apache Hadoop vs. Oracle Big Data Appliance report.
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