Compare Apache Hadoop vs. Oracle Autonomous Data Warehouse

Apache Hadoop is ranked 5th in Data Warehouse with 8 reviews while Oracle Autonomous Data Warehouse is ranked 6th in Cloud Data Warehouse with 4 reviews. Apache Hadoop is rated 7.6, while Oracle Autonomous Data Warehouse is rated 8.8. The top reviewer of Apache Hadoop writes "An inexpensive and flexible suite that helps users integrate varied legacy systems". On the other hand, the top reviewer of Oracle Autonomous Data Warehouse writes "Saves time by allowing me to simply load my data and go". Apache Hadoop is most compared with Snowflake, VMware Tanzu Greenplum and Oracle Exadata, whereas Oracle Autonomous Data Warehouse is most compared with Snowflake, Microsoft Azure SQL Data Warehouse and Amazon Redshift.
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Most Helpful Review
Find out what your peers are saying about Snowflake Computing, Microsoft, Micro Focus and others in Cloud Data Warehouse. Updated: March 2020.
406,860 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
The most valuable features are powerful tools for ingestion, as data is in multiple systems.The most valuable feature is the database.It's good for storing historical data and handling analytics on a huge amount of data.The ability to add multiple nodes without any restriction is the solution's most valuable aspect.What comes with the standard setup is what we mostly use, but Ambari is the most important.The best thing about this solution is that it is very powerful and very cheap.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.Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing.

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The analytics have been very good. We've found them to be quite useful.I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system.I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW.Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets.

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Cons
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.It would be good to have more advanced analytics tools.The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment.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 upgrade path should be improved because it is not as easy as it should be.We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it.I would like to see more direct integration of visualization applications.

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Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable.I would like to see an on-premise solution in the future.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.An improvement for us would be the inclusion of support for an internal IP, so we could use it directly with the VCN in Oracle Cloud.

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Pricing and Cost Advice
This is a low cost and powerful solution.

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The cost is perfect with Oracle Universal credit.

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Ranking
5th
out of 31 in Data Warehouse
Views
13,336
Comparisons
11,258
Reviews
8
Average Words per Review
399
Avg. Rating
7.6
6th
Views
2,061
Comparisons
1,300
Reviews
4
Average Words per Review
366
Avg. Rating
8.8
Top Comparisons
Compared 32% of the time.
Compared 14% of the time.
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Overview
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Autonomous Data Warehouse is market-leading Oracle Database software running on proven Oracle Exadata infrastructure that is optimized to deliver unbeatable performance for data warehouse workloads. Built-in adaptive machine learning eliminates manual labor for administrative management. With Oracle, business and enterprise users can now build their own data warehouse, data mart, or sandbox in a few minutes.

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Sample Customers
Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web LabHertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
Top Industries
VISITORS READING REVIEWS
Software R&D Company35%
Comms Service Provider16%
Financial Services Firm14%
Government6%
VISITORS READING REVIEWS
Software R&D Company62%
Comms Service Provider10%
K 12 Educational Company Or School4%
Construction Company4%
Find out what your peers are saying about Snowflake Computing, Microsoft, Micro Focus and others in Cloud Data Warehouse. Updated: March 2020.
406,860 professionals have used our research since 2012.
We monitor all Cloud 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.