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."We selected Apache Hadoop because it is not dependent on third-party vendors."
"It's open-source, so it's very cost-effective."
"One valuable feature is that we can download data."
"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."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"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."
"Hadoop File System is compatible with almost all the query engines."
"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."
"This is a comprehensive solution that is easy to deploy."
"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."
"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."
"It needs better user interface (UI) functionalities."
"Hadoop's security could be better."
"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"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."
"General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error."
"I would like to see more direct integration of visualization applications."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
"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."
Apache Hadoop is ranked 5th in Data Warehouse with 33 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 AWS Lake Formation, 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.
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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.
