We performed a comparison between Apache Hadoop and Oracle Exadata 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."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."
"The most valuable feature is the database."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"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."
"The best thing about this solution is that it is very powerful and very cheap."
"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."
"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."
"The most valuable feature of Oracle Exadata is its capabilities for storing and processing data. It is very good for our domain."
"The ease of setup is an eight out of ten."
"We like the tool’s features like Smart Scan, Hybrid Columnar Compression, and the TFA."
"The data replication is very good."
"Exadata's best features are its performance during redo logging and the elasticity of the database handling."
"Exadata is a fantastic machine. Two features stand out. The first is the resource input/output management tool that allows you to manage the resources to the neck on the Exadata box."
"It has improved the performance, now we run with more performance cores with less CPU to attend all the database demands. Reducing Time to Market, increase our ability to face the competition with speed and low cost."
"The tool's performance is good."
"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 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."
"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."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"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."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"The solution's pricing is very high."
"License or upgrade management can be difficult and time consuming because it requires login to a separate console."
"The initial setup process is very difficult and extremely complex."
"There's room for improvement in terms of deployment, as it could be made faster and more user-friendly."
"Certification should also be improved. Today, Oracle doesn't certify applications with engineered systems."
"The solution lacks a visualized console."
"We have experienced some issues with processing unstructured data on Exadata. This is an important requirement for our AIML based use case. Reactive analytics data can not be prepared easily in Oracle Exadata."
"I liked Spark, but it was discontinued when Exadata L6 came back. I loved it, and I wish they would bring back Spark integration."
Apache Hadoop is ranked 5th in Data Warehouse with 31 reviews while Oracle Exadata is ranked 2nd in Data Warehouse with 124 reviews. Apache Hadoop is rated 7.8, while Oracle Exadata is rated 8.4. 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 Oracle Exadata writes "Very fast, scalable, stable, and demonstrates good performance". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Azure Data Factory, Snowflake, Teradata and BigQuery, whereas Oracle Exadata is most compared with Oracle Database Appliance, Teradata, Oracle Autonomous Data Warehouse, Snowflake and IBM Netezza Performance Server. See our Apache Hadoop vs. Oracle Exadata report.
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