Apache Hadoop vs. Oracle Autonomous Data Warehouse

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.3 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
Oracle Autonomous Data Warehouse
Score 9.0 out of 10
N/A
Oracle Autonomous Data Warehouse is optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can discover business insights using data of any size and type. The solution is built for the cloud and optimized using Oracle Exadata.N/A
Pricing
Apache HadoopOracle Autonomous Data Warehouse
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HadoopOracle Autonomous Data Warehouse
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HadoopOracle Autonomous Data Warehouse
Considered Both Products
Hadoop

No answer on this topic

Oracle Autonomous Data Warehouse
Chose Oracle Autonomous Data Warehouse
Hadoop still being a naive field, we have very few expertise with great knowledge in Hadoop. Oracle Data Warehouse does not support unstructured data, where as Hadoop does. There are a lot of functionalities which Oracle Data Warehouse provides, which makes us us not to go for H…
Chose Oracle Autonomous Data Warehouse
Oracle Data Warehouse became immediate selection whenever we were implementing BI solutions with Dimension Modeling and Oracle based Transactional Systems, compared to other places where we used Teradata and Netezza with 3NF model structure for BI solutions. For other various …
Chose Oracle Autonomous Data Warehouse
Oracle is a lot cheaper than traditional data warehouse appliance solutions, even if you get an expensive DBA who knows what he/she is doing. It definitely takes a lot more work to ensure it scales as your data size grows. While it won't scale past the terabyte sized data sets, …
Top Pros
Top Cons
Best Alternatives
Apache HadoopOracle Autonomous Data Warehouse
Small Businesses

No answers on this topic

Google BigQuery
Google BigQuery
Score 8.6 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
Oracle Exadata
Oracle Exadata
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopOracle Autonomous Data Warehouse
Likelihood to Recommend
8.9
(36 ratings)
8.9
(32 ratings)
Likelihood to Renew
9.6
(8 ratings)
8.0
(1 ratings)
Usability
8.5
(5 ratings)
-
(0 ratings)
Performance
8.0
(1 ratings)
-
(0 ratings)
Support Rating
7.5
(3 ratings)
-
(0 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
Implementation Rating
-
(0 ratings)
9.0
(1 ratings)
User Testimonials
Apache HadoopOracle Autonomous Data Warehouse
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Oracle
II would recommend Oracle Autonomous Data Warehouse to someone looking to fully automate the transferring of data especially in a warehouse scenario though I can see the elasticity of the suite that is offered and can see it is applicable in other scenarios not just warehouses.
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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Oracle
  • Very easy and fast to load data into the Oracle Autonomous Data Warehouse
  • Exceptionally fast retrieval of data joining 100 million row table with a billion row table plus the size of the database was reduced by a factor of 10 due to how Oracle store[s] and organise[s] data and indexes.
  • Flexibility with scaling up and down CPU on the fly when needed, and just stop it when not needed so you don't get charged when it is not running.
  • It is always patched and always available and you can add storage dynamically as you need it.
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Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Oracle
  • It is very expensive product. But not to mention, there's good reasons why it is expensive.
  • The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
  • Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.
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Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Oracle
Because
  • It is really simple to provision and configure.
  • Does not require continous attention from the DBA, autonomous features allows the database to perform most of the regular admin tasks without need for human intervention.
  • Allows to integrate multiple data sources on a central data warehouse, and explode the information stored with different analytic and reporting tools.
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Usability
Apache
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
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Oracle
No answers on this topic
Support Rating
Apache
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
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Oracle
No answers on this topic
Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Oracle
No answers on this topic
Implementation Rating
Apache
No answers on this topic
Oracle
Understanding Oracle Cloud Infrastructure is really simple, and Autonomous databases are even more. Using shared or dedicated infrastructure is one of the few things you need to consider at the moment of starting provisioning your Oracle Autonomous Data Warehouse.
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Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Oracle
As I mentioned, I have also worked with Amazon Redshift, but it is not as versatile as Oracle Autonomous Data Warehouse and does not provide a large variety of products. Oracle Autonomous Data Warehouse is also more reliable than Amazon Redshift, hence why I have chosen it
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Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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Oracle
  • Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
  • Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
  • All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.
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