Compare Apache Hadoop vs. Oracle Autonomous Data Warehouse

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Top Review
Find out what your peers are saying about Snowflake Computing, Oracle, Micro Focus and others in Data Warehouse. Updated: September 2021.
535,015 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
"What comes with the standard setup is what we mostly use, but Ambari is the most important.""The ability to add multiple nodes without any restriction is the solution's most valuable aspect.""It's good for storing historical data and handling analytics on a huge amount of data.""The most valuable feature is the database.""The most valuable features are powerful tools for ingestion, as data is in multiple systems.""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.""The performance is pretty good.""Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."

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"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system.""The analytics have been very good. We've found them to be quite useful.""It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues.""Self-patching and runs machine-learning across its logs all the time""The solution integrates well with Power BI.""The performance and scalability are awesome."

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Cons
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency.""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.""It would be good to have more advanced analytics tools.""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.""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.""The solution is very expensive.""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."

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"I would like to see an on-premise solution in the future.""Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable.""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.""Ease of connectivity could be improved.""The initial setup was pretty complex. It was not easy.""It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."

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Pricing and Cost Advice
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"ROI is high.""You pay as you go, and you don't pay for services that you don't use."

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Questions from the Community
Top Answer: I don't think using Apache Spark without Hadoop has any major drawbacks or issues. I have used Apache Spark quite successfully with AWS S3 on many projects which are batch based. Yes for very high… more »
Top Answer: Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability.
Top Answer: The performance and scalability are awesome.
Top Answer: You pay as you go, and you don't pay for services that you don't use. If you feel that you need additional resources then you can increase them and pay only for them. There is no need to worry about… more »
Top Answer: It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment. On-premises, you can integrate with different vendors such as Microsoft. There… more »
Ranking
7th
out of 30 in Data Warehouse
Views
8,334
Comparisons
6,794
Reviews
8
Average Words per Review
429
Rating
7.5
6th
Views
5,063
Comparisons
3,762
Reviews
6
Average Words per Review
538
Rating
8.3
Comparisons
Learn More
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 Lab
Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
Top Industries
VISITORS READING REVIEWS
Computer Software Company30%
Comms Service Provider17%
Financial Services Firm13%
Energy/Utilities Company5%
VISITORS READING REVIEWS
Computer Software Company49%
Comms Service Provider12%
Financial Services Firm4%
Government4%
Company Size
REVIEWERS
Small Business37%
Midsize Enterprise21%
Large Enterprise42%
REVIEWERS
Small Business44%
Large Enterprise56%
Find out what your peers are saying about Snowflake Computing, Oracle, Micro Focus and others in Data Warehouse. Updated: September 2021.
535,015 professionals have used our research since 2012.

Apache Hadoop is ranked 7th in Data Warehouse with 8 reviews while Oracle Autonomous Data Warehouse is ranked 6th in Cloud Data Warehouse with 6 reviews. Apache Hadoop is rated 7.6, while Oracle Autonomous Data Warehouse is rated 8.4. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". On the other hand, the top reviewer of Oracle Autonomous Data Warehouse writes "Self-patching means I generally don't need a DBA; detailed analytics make it very capable". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Snowflake, VMware Tanzu Greenplum, Oracle Exadata and SAP BW4HANA, whereas Oracle Autonomous Data Warehouse is most compared with Snowflake, Microsoft Azure Synapse Analytics, Amazon Redshift, Oracle Exadata and Oracle Exadata Express Cloud Service.

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.