We performed a comparison between Apache Hadoop and Oracle Autonomous Data Warehouse based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."
"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 performance is pretty good."
"The tool's stability is good."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"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."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"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 performance and scalability are awesome."
"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."
"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."
"With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main reason we use it."
"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."
"Self-patching and runs machine-learning across its logs all the time"
"I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."
"A very good integration feature that restricts access to unauthorized people."
"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."
"It needs better user interface (UI) functionalities."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"It could be more user-friendly."
"Since it is an open-source product, there won't be much support."
"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."
"The stability of the solution needs improvement."
"It would be good to have more advanced analytics tools."
"The initial setup was pretty complex. It was not easy."
"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."
"I would like to see an on-premise solution in the future."
"It doesn't work well when you have unstructured data or you need online analytics. It is not as nice as Hadoop in these aspects."
"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."
"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace."
"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."
"The solution lacks visibility options."
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Apache Hadoop is ranked 5th in Data Warehouse with 33 reviews while Oracle Autonomous Data Warehouse is ranked 10th in Cloud Data Warehouse with 16 reviews. Apache Hadoop is rated 7.8, while Oracle Autonomous Data Warehouse is rated 8.6. 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 Autonomous Data Warehouse writes "A tool for data warehousing that offers scalability, stability, and ease of setup". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Oracle Autonomous Data Warehouse is most compared with Oracle Exadata, Snowflake, Microsoft Azure Synapse Analytics, BigQuery and Azure Data Factory. See our Apache Hadoop vs. Oracle Autonomous Data Warehouse report.
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