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."The most valuable feature is the database."
"Hadoop is extensible — it's elastic."
"The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."
"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."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies."
"It's good for storing historical data and handling analytics on a huge amount of data."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"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."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"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."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"Since it is an open-source product, there won't be much support."
"I would like to see more direct integration of visualization applications."
"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."
"The product should be simplified for the average user."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
Apache Hadoop is ranked 5th in Data Warehouse with 34 reviews while Oracle Big Data Appliance is ranked 14th in Data Warehouse with 5 reviews. 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, Microsoft Azure Synapse Analytics and Teradata. See our Apache Hadoop vs. Oracle Big Data Appliance report.
See our list of best Data Warehouse vendors.
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.